Mitigation of latency disparity in a data transaction processing system

ABSTRACT

A data transaction processing system receives electronic data transaction request messages from client computers over a data communication network and groups a subset of the electronic data transaction request messages at varying intervals. The intervals may be dynamically determined and may be based on the volume and rate of the incoming electronic data transaction request messages. The data transaction processing system may preprocess the group of electronic data transaction request messages before forwarding the electronic data transaction request messages to a transaction processor, which processes the subset of electronic data transaction request messages in a non-chronological order.

REFERENCE TO RELATED APPLICATIONS

This application is a continuation under 37 C.F.R. 1.53(b) of U.S.patent application Ser. No. 15/581,492 filed Apr. 28, 2017, now U.S.Pat. No. 10,432,565 which claims the benefit of the filing date under 35U.S.C. § 119(e) of U.S. Provisional Patent Application Ser. No.62/470,593, filed Mar. 13, 2017, which are both hereby incorporated byreference in their entirety and relied upon.

BACKGROUND

A data transaction processing system receives electronic datatransaction request messages from client computers specifyingtransactions to be performed. Data transaction processing systemstypically process electronic data transaction request messages as theyare received. The speed at which client computers can transmitelectronic data transaction request messages to the data transactionprocessing system thus becomes a critical component of transactionexecution. Client computers are incentivized to obtain and maintain fastnetwork connections to the data transaction processing system. The costof continuously obtaining and maintaining the newest technologies canbecome prohibitive for client computers. The data transaction processingsystem must also continually invest computing resources into itstechnology infrastructure to receive and process electronic datatransaction request messages.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a computer network system, according to some embodiments.

FIG. 2 depicts a general computer system, according to some embodiments.

FIG. 3A depicts a storage data structure, according to some embodiments.

FIG. 3B depicts an alternative storage data structure, according to someembodiments.

FIG. 3C depicts an order book data structure, according to someembodiments.

FIG. 4 depicts a match engine module, according to some embodiments.

FIG. 5 depicts a message management module, according to someembodiments.

FIG. 6 depicts a buffer in a message management module, according tosome embodiments.

FIG. 7 depicts a buffer and sequencer in a message management module,according to some embodiments.

FIG. 8 also depicts a buffer and sequencer in a message managementmodule, according to some embodiments.

FIG. 9 depicts a high-level flowchart illustrating a method formitigating disparities in latencies of electronic data transactionrequest messages by a data transaction processing system, according tosome embodiments.

FIG. 10 depicts another message management module, according to someembodiments.

FIGS. 11A to 11C depict an example buffer containing electronic datatransaction request messages that are compressed, according to someembodiments.

FIGS. 12A to 12C depict an example buffer containing electronic datatransaction request messages that are compressed, according to someembodiments.

FIGS. 13A to 13C depict an example buffer containing electronic datatransaction request messages that are compressed, according to someembodiments.

FIG. 14 depicts a high-level flowchart illustrating a method forprocessing electronic data transaction request messages in a datatransaction processing system, according to some embodiments.

DETAILED DESCRIPTION

The disclosed embodiments relate generally to a data transactionprocessing system that receives electronic data transaction requestmessages from client computers including requests to performtransactions on data objects. Different client computers may connect tothe data transaction processing system over different communicationsinfrastructures and/or at different speeds, thus experiencing varyinglatencies. The data transaction processing system mitigates disparitiesin the latencies between client computers and the data transactionprocessing system, which may otherwise result in disparities in the timeof processing of competing messages. Moreover, different clientcomputers receive information (e.g., common/public information, e.g.,news from other trading platforms external to an exchange computingsystem) at different speeds, which creates an information differencebetween client computers. Many of the client computers electronic datatransaction request messages are based on such common/publicinformation. The data transaction processing system also mitigatesdisparities in the latencies between client computers receivingcommon/public information.

The disclosed embodiments may mitigate such disparities by buffering orotherwise grouping or collecting, e.g. into a bucket, group, set, orother collection, e.g., automatically, temporally proximate competingmessages together as they are received and subsequently arbitrating,e.g., automatically, among those grouped competing messages, in a mannerother than solely based on the order in which the competing messages inthe group were received. The grouping of electronic data transactionrequest messages may vary based on or otherwise subject to the controlof an interval processor. The disclosed embodiments mitigate the need orbenefits of client computers to continually invest in computingresources to gain a competitive advantage over competing electronic datatransaction request messages. For more information on competingmessages/transactions transmitted to an exchange computing system, seeU.S. Patent Publication No. 2017/0046783, the entirety of which isincorporated by reference herein and relied upon.

The data transaction processing system in one embodiment also minimizesthe amount of processing, e.g., due to redundant or conflictinginstructions, performed on electronic data transaction request messagesthat are grouped together, thus reducing the computing load of a matchengine module of the data transaction processing system. In oneembodiment, the data transaction processing system compresses messagesin a buffer before they are forwarded to the transaction processor.

The data transaction processing system, may, in one embodiment, operatein a stateful manner, i.e., depend upon historical/prior messagesreceived, and/or rely upon previous results thereof or previousdecisions made, by the transaction processing system. The datatransaction processing system may also access data structures storinginformation about a current environment state to determine if orders ormessages match.

The disclosed embodiments also improve upon the technical field ofnetworking by reducing incentives to maintain and operate the fastestconnections between client computers and the data transaction processingsystem. The disclosed system is a specific implementation and practicalapplication of a hardware matching processor that processes electronicdata transaction request messages in varying, unpredictable group sizes.

The disclosed embodiments may reduce congestion (a high volume ofsubstantially simultaneously received transactions) at the networkingress point, which may result in reducing denial of service, packetloss, and corresponding retries by senders.

At least some of the problems solved by the disclosed encoding systemare specifically rooted in technology, e.g., electronic data transactionrequest messages that are transmitted to a data transaction processingsystem experience varying latencies, and network latency andtransmission speed greatly impact the execution/processing of theelectronic data transaction request messages, and are solved by means ofa technical solution, e.g., grouping and sorting electronic datatransaction request messages in a systematic, but dynamic andunpredictable, manner to mitigate the effects of transmission latency onthe execution and performance of the electronic data transaction requestmessages.

Accordingly, the resulting problem is a problem arising in computersystems due to the impact of network latency on the execution/processingof electronic data transaction request messages, which overemphasizesthe need for client computers to continually invest computing resourcesto operate and maintain a fast technology infrastructure. The solutionsdisclosed herein are, in one embodiment, implemented as automaticresponses and actions by an exchange computing system computer.

The disclosed embodiments may disincentivize rapid transactionsubmission by market participants, which may reduce the need for marketparticipants to operate and maintain exceedingly high-speed transmissionconnections to the data transaction processing system. For example, thedisclosed embodiments may implement a latency floor or a minimum latencythat minimizes the need to submit, or advantage conferred uponsubmitting, electronic data transaction request messages in less timethan the latency floor. The disclosed embodiments change traditionalincentives of traders in order to influence their behavior (e.g.,transaction submission) in a manner which facilitates and results in thestated performance enhancements. The data transaction processing system,as a system which processes externally and independently generatedtransactions, is decoupled from the entities/systems which generate andsubmit transactions processing, e.g., it cannot control the message flowor rate of messages transmitted by market participants. The disclosedembodiments enable the data transaction processing system to influencethe behavior (e.g., transaction submission) of these decoupledsystems/entities, e.g., the traders, in a manner that facilitates and/orresults in the stated performance enhancements

The disclosed embodiments may be directed to an exchange computingsystem that includes multiple hardware matching processors that match,or attempt to match, electronic data transaction request messages withother electronic data transaction request messages counter (or contra)thereto. Incoming electronic data transaction request messages may bereceived from different client computers over a data communicationnetwork and output electronic data transaction result messages may betransmitted to the client computers and may be indicative of results ofthe attempts to match incoming electronic data transaction requestmessages.

The disclosed embodiments may be implemented in a data transactionprocessing system that processes data items or objects. Customer or userdevices (e.g., client computers) may submit electronic data transactionrequest messages, e.g., inbound messages, to the data transactionprocessing system over a data communication network. The electronic datatransaction request messages may include, for example, transactionmatching parameters, such as instructions and/or values, for processingthe data transaction request messages within the data transactionprocessing system. The instructions may be to perform transactions,e.g., buy or sell a quantity of a product at a range of values definedequations. Products, e.g., financial instruments, or order booksrepresenting the state of an electronic marketplace for a product, maybe represented as data objects within the exchange computing system. Theinstructions may also be conditional, e.g., buy or sell a quantity of aproduct at a given value if a trade for the product is executed at someother reference value. The data transaction processing system mayinclude various specifically configured matching processors that match,e.g., automatically, electronic data transaction request messages forthe same one of the data items or objects. The specifically configuredmatching processors may match, or attempt to match, electronic datatransaction request messages based on multiple transaction matchingparameters from the different client computers. The specificallyconfigured matching processors may additionally generate informationindicative of a state of an environment (e.g., the state of the orderbook) based on the processing and report this information to datarecipient computing systems via outbound messages published via one ormore data feeds.

For example, one exemplary environment where the disclosed embodimentsmay be desirable is in financial markets, and in particular, electronicfinancial exchanges, such as a futures exchange, such as the ChicagoMercantile Exchange Inc. (CME).

Exchange Computing System

A financial instrument trading system, such as a futures exchange, suchas the Chicago Mercantile Exchange Inc. (CME), provides a contractmarket where financial instruments, e.g., futures and options onfutures, are traded using electronic systems. “Futures” is a term usedto designate all contracts for the purchase or sale of financialinstruments or physical commodities for future delivery or cashsettlement on a commodity futures exchange. A futures contract is alegally binding agreement to buy or sell a commodity at a specifiedprice at a predetermined future time. An option contract is the right,but not the obligation, to sell or buy the underlying instrument (inthis case, a futures contract) at a specified price on or before acertain expiration date. An option contract offers an opportunity totake advantage of futures price moves without actually having a futuresposition. The commodity to be delivered in fulfillment of the contract,or alternatively the commodity for which the cash market price shalldetermine the final settlement price of the futures contract, is knownas the contract's underlying reference or “underlier.” The underlying orunderlier for an options contract is the corresponding futures contractthat is purchased or sold upon the exercise of the option.

The terms and conditions of each futures contract are standardized as tothe specification of the contract's underlying reference commodity, thequality of such commodity, quantity, delivery date, and means ofcontract settlement. Cash settlement is a method of settling a futurescontract whereby the parties effect final settlement when the contractexpires by paying/receiving the loss/gain related to the contract incash, rather than by effecting physical sale and purchase of theunderlying reference commodity at a price determined by the futurescontract, price. Options and futures may be based on more generalizedmarket indicators, such as stock indices, interest rates, futurescontracts, and other derivatives.

An exchange may provide for a centralized “clearing house” through whichtrades made must be confirmed, matched, and settled each day untiloffset or delivered. The clearing house may be an adjunct to anexchange, and may be an operating division of an exchange, which isresponsible for settling trading accounts, clearing trades, collectingand maintaining performance bond funds, regulating delivery, andreporting trading data. One of the roles of the clearing house is tomitigate credit risk. Clearing is the procedure through which theclearing house becomes buyer to each seller of a futures contract, andseller to each buyer, also referred to as a novation, and assumesresponsibility for protecting buyers and sellers from financial loss dueto breach of contract, by assuring performance on each contract. Aclearing member is a firm qualified to clear trades through the clearinghouse.

An exchange computing system may operate under a central counterpartymodel, where the exchange acts as an intermediary between marketparticipants for the transaction of financial instruments. Inparticular, the exchange computing system novates itself into thetransactions between the market participants, i.e., splits a giventransaction between the parties into two separate transactions where theexchange computing system substitutes itself as the counterparty to eachof the parties for that part of the transaction, sometimes referred toas a novation. In this way, the exchange computing system acts as aguarantor and central counterparty and there is no need for the marketparticipants to disclose their identities to each other, or subjectthemselves to credit or other investigations by a potentialcounterparty. For example, the exchange computing system insulates onemarket participant from the default by another market participant.Market participants need only meet the requirements of the exchangecomputing system. Anonymity among the market participants encourages amore liquid market environment as there are lower barriers toparticipation. The exchange computing system can accordingly offerbenefits such as centralized and anonymous matching and clearing.

A match engine within a financial instrument trading system may comprisea transaction processing system that processes a high volume, e.g.,millions, of messages or orders in one day. The messages are typicallysubmitted from market participant computers. Exchange match enginesystems may be subject to variable messaging loads due to variablemarket messaging activity. Performance of a match engine depends to acertain extent on the magnitude of the messaging load and the workneeded to process that message at any given time. An exchange matchengine may process large numbers of messages during times of high-volumemessaging activity. With limited processing capacity, high messagingvolumes may increase the response time or latency experienced by marketparticipants.

The disclosed embodiments recognize that electronic messages such asincoming messages from market participants, i.e., “outright” messages,e.g., trade order messages, etc., are sent from client devicesassociated with market participants, or their representatives, to anelectronic trading or market system. For example, a market participantmay submit an electronic message to the electronic trading system thatincludes an associated specific action to be undertaken by theelectronic trading system, such as entering a new trade order into themarket or modifying an existing order in the market. In one embodiment,if a participant wishes to modify a previously sent request, e.g., aprior order which has not yet been processed or traded, they may send arequest message comprising a request to modify the prior request.

Electronic Data Transaction Request Messages

As used herein, a financial message, or an electronic message, refersboth to messages communicated by market participants to an electronictrading or market system and vice versa. The messages may becommunicated using packeting or other techniques operable to communicateinformation between systems and system components. Some messages may beassociated with actions to be taken in the electronic trading or marketsystem. In particular, in one embodiment, upon receipt of a request, atoken is allocated and included in a TCP shallow acknowledgmenttransmission sent back to the participant acknowledging receipt of therequest. It should be appreciated that while this shallow acknowledgmentis, in some sense, a response to the request, it does not confirm theprocessing of an order included in the request. The participant, i.e.,their device, then sends back a TCP acknowledgment which acknowledgesreceipt of the shallow acknowledgment and token.

Financial messages communicated to the electronic trading system, alsoreferred to as “inbound” messages, may include associated actions thatcharacterize the messages, such as trader orders, order modifications,order cancellations and the like, as well as other message types.Inbound messages may be sent from market participants, or theirrepresentatives, e.g., trade order messages, etc., to an electronictrading or market system. For example, a market participant may submitan electronic message to the electronic trading system that includes anassociated specific action to be undertaken by the electronic tradingsystem, such as entering a new trade order into the market or modifyingan existing order in the market. In one exemplary embodiment, theincoming request itself, e.g., the inbound order entry, may be referredto as an iLink message. iLink is a bidirectional communications/messageprotocol/message format implemented by the Chicago Mercantile ExchangeInc.

Financial messages communicated from the electronic trading system,referred to as “outbound” messages, may include messages responsive toinbound messages, such as confirmation messages, or other messages suchas market update messages, quote messages, and the like. Outboundmessages may be disseminated via data feeds.

Financial messages may further be categorized as having or reflecting animpact on a market or electronic marketplace, also referred to as an“order book” or “book,” for a traded product, such as a prevailing pricetherefore, number of resting orders at various price levels andquantities thereof, etc., or not having or reflecting an impact on amarket or a subset or portion thereof. In one embodiment, an electronicorder book may be understood to be an electronic collection of theoutstanding or resting orders for a financial instrument.

For example, a request to place a trade may result in a responseindicative of the trade either being matched with, or being rested on anorder book to await, a suitable counter-order. This response may includea message directed solely to the trader who submitted the order toacknowledge receipt of the order and report whether it was matched, andthe extent thereto, or rested. The response may further include amessage to all market participants reporting a change in the order bookdue to the order. This response may take the form of a report of thespecific change to the order book, e.g., an order for quantity X atprice Y was added to the book (referred to, in one embodiment, as aMarket By Order message), or may simply report the result, e.g., pricelevel Y now has orders for a total quantity of Z (where Z is the sum ofthe previous resting quantity plus quantity X of the new order). In somecases, requests may elicit a non-impacting response, such as temporallyproximate to the receipt of the request, and then cause a separatemarket-impact reflecting response at a later time. For example, a stoporder, fill or kill order (FOK), also known as an immediate or cancelorder, or other conditional request may not have an immediate marketimpacting effect, if at all, until the requisite conditions are met.

An acknowledgement or confirmation of receipt, e.g., a non-marketimpacting communication, may be sent to the trader simply confirmingthat the order was received. Upon the conditions being met and a marketimpacting result thereof occurring, a market-impacting message may betransmitted as described herein both directly back to the submittingmarket participant and to all market participants (in a Market By Price“MBP” e.g., Aggregated By Value (“ABV”) book, or Market By Order “MBO”,e.g., Per Order (“PO”) book format). It should be appreciated thatadditional conditions may be specified, such as a time or price limit,which may cause the order to be dropped or otherwise canceled and thatsuch an event may result in another non-market-impacting communicationinstead. In some implementations, market impacting communications may becommunicated separately from non-market impacting communications, suchas via a separate communications channel or feed.

It should be further appreciated that various types of market data feedsmay be provided which reflect different markets or aspects thereof.Market participants may then, for example, subscribe to receive thosefeeds of interest to them. For example, data recipient computing systemsmay choose to receive one or more different feeds. As market impactingcommunications usually tend to be more important to market participantsthan non-impacting communications, this separation may reduce congestionand/or noise among those communications having or reflecting an impacton a market or portion thereof. Furthermore, a particular market datafeed may only communicate information related to the top buy/sell pricesfor a particular product, referred to as “top of book” feed, e.g., onlychanges to the top 10 price levels are communicated. Such limitationsmay be implemented to reduce consumption of bandwidth and messagegeneration resources. In this case, while a request message may beconsidered market-impacting if it affects a price level other than thetop buy/sell prices, it will not result in a message being sent to themarket participants.

Examples of the various types of market data feeds which may be providedby electronic trading systems, such as the CME, in order to providedifferent types or subsets of market information or to provide suchinformation in different formats include Market By Order or Per Order,Market Depth (also known as Market by Price or Aggregated By Value to adesignated depth of the book), e.g., CME offers a 10-deep market byprice feed, Top of Book (a single depth Market by Price feed), andcombinations thereof. There may also be all manner of specialized feedsin terms of the content, i.e., providing, for example, derived data,such as a calculated index.

Market data feeds may be characterized as providing a “view” or“overview” of a given market, an aggregation or a portion thereof, orchanges thereto. For example, a market data feed, such as a Market ByPrice (“MBP”) feed, also known as an Aggregated By Value (“ABV”) feed,may convey, with each message, the entire/current state of a market, orportion thereof, for a particular product as a result of one or moremarket impacting events. For example, an MBP message may convey a totalquantity of resting buy/sell orders at a particular price level inresponse to a new order being placed at that price. An MBP message mayconvey a quantity of an instrument which was traded in response to anincoming order being matched with one or more resting orders. MBPmessages may only be generated for events affecting a portion of amarket, e.g., only the top 10 resting buy/sell orders and, thereby, onlyprovide a view of that portion. As used herein, a market impactingrequest may be said to impact the “view” of the market as presented viathe market data feed.

An MBP feed may utilize different message formats for conveyingdifferent types of market impacting events. For example, when a neworder is rested on the order book, an MBP message may reflect thecurrent state of the price level to which the order was added, e.g., thenew aggregate quantity and the new aggregate number of resting orders.As can be seen, such a message conveys no information about theindividual resting orders, including the newly rested order, themselvesto the market participants. Only the submitting market participant, whoreceives a separate private message acknowledging the event, knows thatit was their order that was added to the book. Similarly, when a tradeoccurs, an MBP message may be sent which conveys the price at which theinstrument was traded, the quantity traded and the number ofparticipating orders, but may convey no information as to whoseparticular orders contributed to the trade. MBP feeds may further batchreporting of multiple events, i.e., report the result of multiple marketimpacting events in a single message.

Alternatively, a market data feed, referred to as a Market By Order(“MBO”) feed also known as a Per Order (“PO”) feed, may convey datareflecting a change that occurred to the order book rather than theresult of that change, e.g., that order ABC for quantity X was added toprice level Y or that order ABC and order XYZ traded a quantity X at aprice Y. In this case, the MBO message identifies only the change thatoccurred so a market participant wishing to know the current state ofthe order book must maintain their own copy and apply the changereflected in the message to know the current state. As can be seen,MBO/PO messages may carry much more data than MBP/ABV messages becauseMBO/PO messages reflect information about each order, whereas MBP/ABVmessages contain information about orders affecting some predeterminedvalue levels. Furthermore, because specific orders, but not thesubmitting traders thereof, are identified, other market participantsmay be able to follow that order as it progresses through the market,e.g., as it is modified, canceled, traded, etc.

An ABV book data object may include information about multiple values.The ABV book data object may be arranged and structured so thatinformation about each value is aggregated together. Thus, for a givenvalue V, the ABV book data object may aggregate all the information byvalue, such as for example, the number of orders having a certainposition at value V, the quantity of total orders resting at value V,etc. Thus, the value field may be the key, or may be a unique field,within an ABV book data object. In one embodiment, the value for eachentry within the ABV book data object is different. In one embodiment,information in an ABV book data object is presented in a manner suchthat the value field is the most granular field of information.

A PO book data object may include information about multiple orders. ThePO book data object may be arranged and structured so that informationabout each order is represented. Thus, for a given order O, the PO bookdata object may provide all of the information for order O. Thus, theorder field may be the key, or may be a unique field, within a PO bookdata object. In one embodiment, the order ID for each entry within thePO book data object is different. In one embodiment, information in a PObook data object is presented in a manner such that the order field isthe most granular field of information.

Thus, the PO book data object may include data about unique orders,e.g., all unique resting orders for a product, and the ABV book dataobject may include data about unique values, e.g., up to a predeterminedlevel, e.g., top ten price or value levels, for a product.

It should be appreciated that the number, type and manner of market datafeeds provided by an electronic trading system are implementationdependent and may vary depending upon the types of products traded bythe electronic trading system, customer/trader preferences, bandwidthand data processing limitations, etc. and that all such feeds, nowavailable or later developed, are contemplated herein. MBP/ABV andMBO/PO feeds may refer to categories/variations of market data feeds,distinguished by whether they provide an indication of the current stateof a market resulting from a market impacting event (MBP) or anindication of the change in the current state of a market due to amarket impacting event (MBO).

Messages, whether MBO or MBP, generated responsive to market impactingevents which are caused by a single order, such as a new order, an ordercancellation, an order modification, etc., are fairly simple and compactand easily created and transmitted. However, messages, whether MBO orMBP, generated responsive to market impacting events which are caused bymore than one order, such as a trade, may require the transmission of asignificant amount of data to convey the requisite information to themarket participants. For trades involving a large number of orders,e.g., a buy order for a quantity of 5000 which matches 5000 sell orderseach for a quantity of 1, a significant amount of information may needto be sent, e.g., data indicative of each of the 5000 trades that haveparticipated in the market impacting event.

In one embodiment, an exchange computing system may generate multipleorder book objects, one for each type of view that is published orprovided. For example, the system may generate a PO book object and anABV book object. It should be appreciated that each book object, or viewfor a product or market, may be derived from the Per Order book object,which includes all the orders for a given financial product or market.

An inbound message may include an order that affects the PO book object,the ABV book object, or both. An outbound message may include data fromone or more of the structures within the exchange computing system,e.g., the PO book object queues or the ABV book object queues.

Furthermore, each participating trader needs to receive a notificationthat their particular order has traded. Continuing with the example,this may require sending 5001 individual trade notification messages, oreven 10,000+ messages where each contributing side (buy vs. sell) isseparately reported, in addition to the notification sent to all of themarket participants.

As detailed in U.S. Patent Publication No. 2015/0161727, the entirety ofwhich is incorporated by reference herein and relied upon, it may berecognized that trade notifications sent to all market participants mayinclude redundant information repeated for each participating trade anda structure of an MBP trade notification message may be provided whichresults in a more efficient communication of the occurrence of a trade.The message structure may include a header portion which indicates thetype of transaction which occurred, i.e., a trade, as well as othergeneral information about the event, an instrument portion whichcomprises data about each instrument which was traded as part of thetransaction, and an order portion which comprises data about eachparticipating order. In one embodiment, the header portion may include amessage type, Transaction Time, Match Event Indicator, and Number ofMarket Data Entries (“No. MD Entries”) fields. The instrument portionmay include a market data update action indicator (“MD Update Action”),an indication of the Market Data Entry Type (“MD Entry Type”), anidentifier of the instrument/security involved in the transaction(“Security ID”), a report sequence indicator (“Rpt Seq”), the price atwhich the instrument was traded (“MD Entry PX”), the aggregate quantitytraded at the indicated price (“ConsTradeQty”), the number ofparticipating orders (“NumberOfOrders”), and an identifier of theaggressor side (“Aggressor Side”) fields. The order portion may furtherinclude an identifier of the participating order (“Order ID”), describedin more detail below, and the quantity of the order traded (“MD EntrySize”) fields. It should be appreciated that the particular fieldsincluded in each portion are implementation dependent and that differentfields in addition to, or in lieu of, those listed may be includeddepending upon the implementation. It should be appreciated that theexemplary fields can be compliant with the FIX binary and/or FIX/FASTprotocol for the communication of the financial information.

The instrument portion contains a set of fields, e.g., seven fieldsaccounting for 23 bytes, which are repeated for each participatinginstrument. In complex trades, such as trades involving combinationorders or strategies, e.g., spreads, or implied trades, there may bemultiple instruments being exchanged among the parties. In oneembodiment, the order portion includes only one field, accounting for 4bytes, for each participating order which indicates the quantity of thatorder which was traded. As will be discussed below, the order portionmay further include an identifier of each order, accounting for anadditional 8 bytes, in addition to the quantity thereof traded. Asshould be appreciated, data which would have been repeated for eachparticipating order, is consolidated, or otherwise summarized in theheader and instrument portions of the message thereby eliminatingredundant information and, overall, significantly reducing the size ofthe message.

While the disclosed embodiments will be discussed with respect to an MBPmarket data feed, it should be appreciated that the disclosedembodiments may also be applicable to an MBO market data feed.

Market Segment Gateway

In one embodiment, the disclosed system may include a Market SegmentGateway (“MSG”) that is the point of ingress/entry and/oregress/departure for all transactions, i.e., the network traffic/packetscontaining the data therefore, specific to a single market at which theorder of receipt of those transactions may be ascribed. An MSG or MarketSegment Gateway may be utilized for the purpose of deterministicoperation of the market. The electronic trading system may includemultiple markets, and because the electronic trading system includes oneMSG for each market/product implemented thereby, the electronic tradingsystem may include multiple MSGs. For more detail on deterministicoperation in a trading system, see U.S. Patent Publication No.2015/0127513 entitled “Transactionally Deterministic High SpeedFinancial Exchange Having Improved, Efficiency, Communication,Customization, Performance, Access, Trading Opportunities, CreditControls, And Fault Tolerance” and filed on Nov. 7, 2013 (“the '513Publication”), the entire disclosure of which is incorporated byreference herein and relied upon.

For example, a participant may send a request for a new transaction,e.g., a request for a new order, to the MSG. The MSG extracts or decodesthe request message and determines the characteristics of the requestmessage.

The MSG may include, or otherwise be coupled with, a buffer, cache,memory, database, content addressable memory, data store or other datastorage mechanism, or combinations thereof, which stores data indicativeof the characteristics of the request message. The request is passed tothe transaction processing system, e.g., the match engine.

An MSG or Market Segment Gateway may be utilized for the purpose ofdeterministic operation of the market. Transactions for a particularmarket may be ultimately received at the electronic trading system viaone or more points of entry, e.g., one or more communicationsinterfaces, at which the disclosed embodiments apply determinism, whichas described may be at the point where matching occurs, e.g., at eachmatch engine (where there may be multiple match engines, each for agiven product/market, or moved away from the point where matching occursand closer to the point where the electronic trading system firstbecomes “aware” of the incoming transaction, such as the point wheretransaction messages, e.g., orders, ingress the electronic tradingsystem. Generally, the terms “determinism” or “transactionaldeterminism” may refer to the processing, or the appearance thereof, oforders in accordance with defined business rules. Accordingly, as usedherein, the point of determinism may be the point at which theelectronic trading system ascribes an ordering to incomingtransactions/orders relative to other incoming transactions/orders suchthat the ordering may be factored into the subsequent processing, e.g.,matching, of those transactions/orders as will be described. For moredetail on deterministic operation in a trading system, see the '513Publication.

Electronic Trading

Electronic trading of financial instruments, such as futures contracts,is conducted by market participants sending orders, such as to buy orsell one or more futures contracts, in electronic form to the exchange.These electronically submitted orders to buy and sell are then matched,if possible, by the exchange, i.e., by the exchange's matching engine,to execute a trade. Outstanding (unmatched, wholly unsatisfied/unfilledor partially satisfied/filled) orders are maintained in one or more datastructures or databases referred to as “order books,” such orders beingreferred to as “resting,” and made visible, i.e., their availability fortrading is advertised, to the market participants through electronicnotifications/broadcasts, referred to as market data feeds. An orderbook is typically maintained for each product, e.g., instrument, tradedon the electronic trading system and generally defines or otherwiserepresents the state of the market for that product, i.e., the currentprices at which the market participants are willing buy or sell thatproduct. As such, as used herein, an order book for a product may alsobe referred to as a market for that product.

Upon receipt of an incoming order to trade in a particular financialinstrument, whether for a single-component financial instrument, e.g., asingle futures contract, or for a multiple-component financialinstrument, e.g., a combination contract such as a spread contract, amatch engine, as described herein, will attempt to identify a previouslyreceived but unsatisfied order counter thereto, i.e., for the oppositetransaction (buy or sell) in the same financial instrument at the sameor better price (but not necessarily for the same quantity unless, forexample, either order specifies a condition that it must be entirelyfilled or not at all).

Previously received but unsatisfied orders, i.e., orders which eitherdid not match with a counter order when they were received or theirquantity was only partially satisfied, referred to as a partial fill,are maintained by the electronic trading system in an order bookdatabase/data structure to await the subsequent arrival of matchingorders or the occurrence of other conditions which may cause the orderto be modified or otherwise removed from the order book.

If the match engine identifies one or more suitable previously receivedbut unsatisfied counter orders, they, and the incoming order, arematched to execute a trade there between to at least partially satisfythe quantities of one or both the incoming order or the identifiedorders. If there remains any residual unsatisfied quantity of theidentified one or more orders, those orders are left on the order bookwith their remaining quantity to await a subsequent suitable counterorder, i.e., to rest. If the match engine does not identify a suitablepreviously received but unsatisfied counter order, or the one or moreidentified suitable previously received but unsatisfied counter ordersare for a lesser quantity than the incoming order, the incoming order isplaced on the order book, referred to as “resting”, with original orremaining unsatisfied quantity, to await a subsequently receivedsuitable order counter thereto. The match engine then generates matchevent data reflecting the result of this matching process. Othercomponents of the electronic trading system, as will be described, thengenerate the respective order acknowledgment and market data messagesand transmit those messages to the market participants.

Matching, which is a function typically performed by the exchange, is aprocess, for a given order which specifies a desire to buy or sell aquantity of a particular instrument at a particular price, ofseeking/identifying one or more wholly or partially, with respect toquantity, satisfying counter orders thereto, e.g., a sell counter to anorder to buy, or vice versa, for the same instrument at the same, orsometimes better, price (but not necessarily the same quantity), whichare then paired for execution to complete a trade between the respectivemarket participants (via the exchange) and at least partially satisfythe desired quantity of one or both of the order and/or the counterorder, with any residual unsatisfied quantity left to await anothersuitable counter order, referred to as “resting.” A match event mayoccur, for example, when an aggressing order matches with a restingorder. In one embodiment, two orders match because one order includesinstructions for or specifies buying a quantity of a particularinstrument at a particular price, and the other order includesinstructions for or specifies selling a (different or same) quantity ofthe instrument at a same or better price. It should be appreciated thatperforming an instruction associated with a message may includeattempting to perform the instruction. Whether or not an exchangecomputing system is able to successfully perform an instruction maydepend on the state of the electronic marketplace.

While the disclosed embodiments will be described with respect to aproduct by product or market by market implementation, e.g. implementedfor each market/order book, it will be appreciated that the disclosedembodiments may be implemented so as to apply across markets formultiple products traded on one or more electronic trading systems, suchas by monitoring an aggregate, correlated or other derivation of therelevant indicative parameters as described herein.

While the disclosed embodiments may be discussed in relation to futuresand/or options on futures trading, it should be appreciated that thedisclosed embodiments may be applicable to any equity, fixed incomesecurity, currency, commodity, options or futures trading system ormarket now available or later developed. It may be appreciated that atrading environment, such as a futures exchange as described herein,implements one or more economic markets where rights and obligations maybe traded. As such, a trading environment may be characterized by a needto maintain market integrity, transparency, predictability,fair/equitable access, and participant expectations with respectthereto. In addition, it may be appreciated that electronic tradingsystems further impose additional expectations and demands by marketparticipants as to transaction processing speed, latency, capacity, andresponse time, while creating additional complexities relating thereto.Accordingly, as will be described, the disclosed embodiments may furtherinclude functionality to ensure that the expectations of marketparticipants are met, e.g., that transactional integrity and predictablesystem responses are maintained.

Financial instrument trading systems allow traders to submit orders andreceive confirmations, market data, and other information electronicallyvia electronic messages exchanged using a network. Electronic tradingsystems ideally attempt to offer a more efficient, fair and balancedmarket where market prices reflect a true consensus of the value oftraded products among the market participants, where the intentional orunintentional influence of any one market participant is minimized ifnot eliminated, and where unfair or inequitable advantages with respectto information access are minimized if not eliminated.

Electronic marketplaces attempt to achieve these goals by usingelectronic messages to communicate actions and related data of theelectronic marketplace between market participants, clearing firms,clearing houses, and other parties. The messages can be received usingan electronic trading system, wherein an action or transactionassociated with the messages may be executed. For example, the messagemay contain information relating to an order to buy or sell a product ina particular electronic marketplace, and the action associated with themessage may indicate that the order is to be placed in the electronicmarketplace such that other orders which were previously placed maypotentially be matched to the order of the received message. Thus, theelectronic marketplace may conduct market activities through electronicsystems.

Clearing House

The clearing house of an exchange clears, settles and guarantees matchedtransactions in contracts occurring through the facilities of theexchange. In addition, the clearing house establishes and monitorsfinancial requirements for clearing members and conveys certain clearingprivileges in conjunction with the relevant exchange markets.

The clearing house establishes clearing level performance bonds(margins) for all products of the exchange and establishes minimumperformance bond requirements for customers of such products. Aperformance bond, also referred to as a margin requirement, correspondswith the funds that must be deposited by a customer with his or herbroker, by a broker with a clearing member or by a clearing member withthe clearing house, for the purpose of insuring the broker or clearinghouse against loss on open futures or options contracts. This is not apart payment on a purchase. The performance bond helps to ensure thefinancial integrity of brokers, clearing members and the exchange as awhole. The performance bond refers to the minimum dollar depositrequired by the clearing house from clearing members in accordance withtheir positions. Maintenance, or maintenance margin, refers to a sum,usually smaller than the initial performance bond, which must remain ondeposit in the customer's account for any position at all times. Theinitial margin is the total amount of margin per contract required bythe broker when a futures position is opened. A drop-in funds below thislevel requires a deposit back to the initial margin levels, i.e., aperformance bond call. If a customer's equity in any futures positiondrops to or under the maintenance level because of adverse price action,the broker must issue a performance bond/margin call to restore thecustomer's equity. A performance bond call, also referred to as a margincall, is a demand for additional funds to bring the customer's accountback up to the initial performance bond level whenever adverse pricemovements cause the account to go below the maintenance.

The exchange derives its financial stability in large part by removingdebt obligations among market participants as they occur. This isaccomplished by determining a settlement price at the close of themarket each day for each contract and marking all open positions to thatprice, referred to as “mark to market.” Every contract is debited orcredited based on that trading session's gains or losses. As prices movefor or against a position, funds flow into and out of the tradingaccount. In the case of the CME, each business day by 6:40 a.m. Chicagotime, based on the mark-to-the-market of all open positions to theprevious trading day's settlement price, the clearing house pays to orcollects cash from each clearing member. This cash flow, known assettlement variation, is performed by CME's settlement banks based oninstructions issued by the clearing house. All payments to andcollections from clearing members are made in “same-day” funds. Inaddition to the 6:40 a.m. settlement, a daily intra-day mark-to-themarket of all open positions, including trades executed during theovernight GLOBEX®, the CME's electronic trading systems, trading sessionand the current day's trades matched before 11:15 a.m., is performedusing current prices. The resulting cash payments are made intra-day forsame day value. In times of extreme price volatility, the clearing househas the authority to perform additional intra-day mark-to-the-marketcalculations on open positions and to call for immediate payment ofsettlement variation. CME's mark-to-the-market settlement system differsfrom the settlement systems implemented by many other financial markets,including the interbank, Treasury securities, over-the-counter foreignexchange and debt, options, and equities markets, where participantsregularly assume credit exposure to each other. In those markets, thefailure of one participant can have a ripple effect on the solvency ofthe other participants. Conversely, CME's mark-to-the-market system doesnot allow losses to accumulate over time or allow a market participantthe opportunity to defer losses associated with market positions.

While the disclosed embodiments may be described in reference to theCME, it should be appreciated that these embodiments are applicable toany exchange. Such other exchanges may include a clearing house that,like the CME clearing house, clears, settles, and guarantees all matchedtransactions in contracts of the exchange occurring through itsfacilities. In addition, such clearing houses establish and monitorfinancial requirements for clearing members and convey certain clearingprivileges in conjunction with the relevant exchange markets.

The disclosed embodiments are also not limited to uses by a clearinghouse or exchange for purposes of enforcing a performance bond or marginrequirement. For example, a market participant may use the disclosedembodiments in a simulation or other analysis of a portfolio. In suchcases, the settlement price may be useful as an indication of a value atrisk and/or cash flow obligation rather than a performance bond. Thedisclosed embodiments may also be used by market participants or otherentities to forecast or predict the effects of a prospective position onthe margin requirement of the market participant.

Trading Environment

The embodiments may be described in terms of a distributed computingsystem. The particular examples identify a specific set of componentsuseful in a futures and options exchange. However, many of thecomponents and inventive features are readily adapted to otherelectronic trading environments. The specific examples described hereinmay teach specific protocols and/or interfaces, although it should beunderstood that the principles involved may be extended to, or appliedin, other protocols and interfaces.

It should be appreciated that the plurality of entities utilizing orinvolved with the disclosed embodiments, e.g., the market participants,may be referred to by other nomenclature reflecting the role that theparticular entity is performing with respect to the disclosedembodiments and that a given entity may perform more than one roledepending upon the implementation and the nature of the particulartransaction being undertaken, as well as the entity's contractual and/orlegal relationship with another market participant and/or the exchange.

An exemplary trading network environment for implementing tradingsystems and methods is shown in FIG. 1. An exchange computer system 100receives messages that include orders and transmits market data relatedto orders and trades to users, such as via wide area network 162 and/orlocal area network 160 and computer devices 150, 152, 154, 156 and 158,as described herein, coupled with the exchange computer system 100.

Herein, the phrase “coupled with” is defined to mean directly connectedto or indirectly connected through one or more intermediate components.Such intermediate components may include both hardware andsoftware-based components. Further, to clarify the use in the pendingclaims and to hereby provide notice to the public, the phrases “at leastone of <A>, <B>, . . . and <N>” or “at least one of <A>, <B>, <N>, orcombinations thereof” are defined by the Applicant in the broadestsense, superseding any other implied definitions therebefore orhereinafter unless expressly asserted by the Applicant to the contrary,to mean one or more elements selected from the group comprising A, B, .. . and N, that is to say, any combination of one or more of theelements A, B, . . . or N including any one element alone or incombination with one or more of the other elements which may alsoinclude, in combination, additional elements not listed.

The exchange computer system 100 may be implemented with one or moremainframe, desktop, or other computers, such as the example computer 200described herein with respect to FIG. 2. A user database 102 may beprovided which includes information identifying traders and other usersof exchange computer system 100, such as account numbers or identifiers,usernames, and passwords. An account data module 104 may be providedwhich may process account information that may be used during trades.

A match engine module 106 may be included to match bid and offer pricesand may be implemented with software that executes one or morealgorithms for matching bids and offers. A trade database 108 may beincluded to store information identifying trades and descriptions oftrades. In particular, a trade database may store informationidentifying the time that a trade took place and the contract price. Anorder book module 110 may be included to compute or otherwise determinecurrent bid and offer prices, e.g., in a continuous auction market.

A market data module 112 may be included to collect market data andprepare the data for transmission to users.

A risk management module 114 may be included to compute and determine auser's risk utilization in relation to the user's defined riskthresholds. The risk management module 114 may also be configured todetermine risk assessments or exposure levels in connection withpositions held by a market participant. The risk management module 114may be configured to administer, manage, or maintain one or moremargining mechanisms implemented by the exchange computer system 100.Such administration, management or maintenance may include managing anumber of database records reflective of margin accounts of the marketparticipants. In some embodiments, the risk management module 114implements one or more aspects of the disclosed embodiments, including,for instance, principal component analysis (PCA) based margining, inconnection with interest rate swap (IRS) portfolios, as describedherein.

A message management module 116 may be included to, among other things,receive, and extract orders from, electronic data transaction requestmessages. The message management module 116 may define a point ofingress into the exchange computer system 100 where messages are orderedand considered to be received by the system. This may be considered apoint of determinism in the exchange computer system 100 that definesthe earliest point where the system can ascribe an order of receipt toarriving messages. The point of determinism may or may not be at or nearthe demarcation point between the exchange computer system 100 and apublic/internet network infrastructure. The message management module116 processes messages by interpreting the contents of a message basedon the message transmit protocol, such as the transmission controlprotocol (“TCP”), to provide the content of the message for furtherprocessing by the exchange computer system.

The message management module 116 may also be configured to detectcharacteristics of an order for a transaction to be undertaken in anelectronic marketplace. For example, the message management module 116may identify and extract order content such as a price, product, volume,and associated market participant for an order. The message managementmodule 116 may also identify and extract data indicating an action to beexecuted by the exchange computer system 100 with respect to theextracted order. For example, the message management module 116 maydetermine the transaction type of the transaction requested in a givenmessage. A message may include an instruction to perform a type oftransaction. The transaction type may be, in one embodiment, arequest/offer/order to either buy or sell a specified quantity or unitsof a financial instrument at a specified price or value. The messagemanagement module 116 may also identify and extract other orderinformation and other actions associated with the extracted order. Allextracted order characteristics, other information, and associatedactions extracted from a message for an order may be collectivelyconsidered an order as described and referenced herein.

Order or message characteristics may include, for example, the state ofthe system after a message is received, arrival time (e.g., the time amessage arrives at the MSG or Market Segment Gateway), message type(e.g., new, modify, cancel), and the number of matches generated by amessage. Order or message characteristics may also include marketparticipant side (e.g., buyer or seller) or time in force (e.g., a gooduntil end of day order that is good for the full trading day, a gooduntil canceled ordered that rests on the order book until matched, or afill or kill order that is canceled if not filled immediately, or a filland kill order (FOK) that is filled to the maximum amount possible basedon the state of the order book at the time the FOK order is processed,and any remaining or unfilled/unsatisfied quantity is not stored on thebooks or allowed to rest).

An order processing module 118 may be included to decompose delta-based,spread instrument, bulk, and other types of composite orders forprocessing by the order book module 110 and/or the match engine module106. The order processing module 118 may also be used to implement oneor more procedures related to clearing an order. The order may becommunicated from the message management module 118 to the orderprocessing module 118. The order processing module 118 may be configuredto interpret the communicated order, and manage the ordercharacteristics, other information, and associated actions as they areprocessed through an order book module 110 and eventually transacted onan electronic market. For example, the order processing module 118 maystore the order characteristics and other content and execute theassociated actions. In an embodiment, the order processing module mayexecute an associated action of placing the order into an order book foran electronic trading system managed by the order book module 110. In anembodiment, placing an order into an order book and/or into anelectronic trading system may be considered a primary action for anorder. The order processing module 118 may be configured in variousarrangements and may be configured as part of the order book module 110,part of the message management module 118, or as an independentfunctioning module.

As an intermediary to electronic trading transactions, the exchangebears a certain amount of risk in each transaction that takes place. Tothat end, the clearing house implements risk management mechanisms toprotect the exchange. One or more of the modules of the exchangecomputer system 100 may be configured to determine settlement prices forconstituent contracts, such as deferred month contracts, of spreadinstruments, such as for example, settlement module 120. A settlementmodule 120 (or settlement processor or other payment processor) may beincluded to provide one or more functions related to settling orotherwise administering transactions cleared by the exchange. Settlementmodule 120 of the exchange computer system 100 may implement one or moresettlement price determination techniques. Settlement-related functionsneed not be limited to actions or events occurring at the end of acontract term. For instance, in some embodiments, settlement-relatedfunctions may include or involve daily or other mark to marketsettlements for margining purposes. In some cases, the settlement module120 may be configured to communicate with the trade database 108 (or thememory(ies) on which the trade database 108 is stored) and/or todetermine a payment amount based on a spot price, the price of thefutures contract or other financial instrument, or other price data, atvarious times. The determination may be made at one or more points intime during the term of the financial instrument in connection with amargining mechanism. For example, the settlement module 120 may be usedto determine a mark to market amount on a daily basis during the term ofthe financial instrument. Such determinations may also be made on asettlement date for the financial instrument for the purposes of finalsettlement.

In some embodiments, the settlement module 120 may be integrated to anydesired extent with one or more of the other modules or processors ofthe exchange computer system 100. For example, the settlement module 120and the risk management module 114 may be integrated to any desiredextent. In some cases, one or more margining procedures or other aspectsof the margining mechanism(s) may be implemented by the settlementmodule 120.

One or more of the above-described modules of the exchange computersystem 100 may be used to gather or obtain data to support thesettlement price determination, as well as a subsequent marginrequirement determination. For example, the order book module 110 and/orthe market data module 112 may be used to receive, access, or otherwiseobtain market data, such as bid-offer values of orders currently on theorder books. The trade database 108 may be used to receive, access, orotherwise obtain trade data indicative of the prices and volumes oftrades that were recently executed in a number of markets. In somecases, transaction data (and/or bid/ask data) may be gathered orobtained from open outcry pits and/or other sources and incorporatedinto the trade and market data from the electronic trading system(s).

It should be appreciated that concurrent processing limits may bedefined by or imposed separately or in combination on one or more of thetrading system components, including the user database 102, the accountdata module 104, the match engine module 106, the trade database 108,the order book module 110, the market data module 112, the riskmanagement module 114, the message management module 116, the orderprocessing module 118, the settlement module 120, or other component ofthe exchange computer system 100.

The disclosed mechanisms may be implemented at any logical and/orphysical point(s), or combinations thereof, at which the relevantinformation/data (e.g., message traffic and responses thereto) may bemonitored or flows or is otherwise accessible or measurable, includingone or more gateway devices, modems, the computers or terminals of oneor more market participants, e.g., client computers, etc.

One skilled in the art will appreciate that one or more modulesdescribed herein may be implemented using, among other things, atangible computer-readable medium comprising computer-executableinstructions (e.g., executable software code). Alternatively, modulesmay be implemented as software code, firmware code, specificallyconfigured hardware or processors, and/or a combination of theaforementioned. For example, the modules may be embodied as part of anexchange 100 for financial instruments. It should be appreciated thedisclosed embodiments may be implemented as a different or separatemodule of the exchange computer system 100, or a separate computersystem coupled with the exchange computer system 100 so as to haveaccess to margin account record, pricing, and/or other data. Asdescribed herein, the disclosed embodiments may be implemented as acentrally accessible system or as a distributed system, e.g., where someof the disclosed functions are performed by the computer systems of themarket participants.

The trading network environment shown in FIG. 1 includes exemplarycomputer devices 150, 152, 154, 156 and 158 which depict differentexemplary methods or media by which a computer device may be coupledwith the exchange computer system 100 or by which a user maycommunicate, e.g., send and receive, trade or other informationtherewith. It should be appreciated that the types of computer devicesdeployed by traders and the methods and media by which they communicatewith the exchange computer system 100 is implementation dependent andmay vary and that not all of the depicted computer devices and/ormeans/media of communication may be used and that other computer devicesand/or means/media of communications, now available or later developedmay be used. Each computer device, which may comprise a computer 200described in more detail with respect to FIG. 2, may include a centralprocessor, specifically configured or otherwise, that controls theoverall operation of the computer and a system bus that connects thecentral processor to one or more conventional components, such as anetwork card or modem. Each computer device may also include a varietyof interface units and drives for reading and writing data or files andcommunicating with other computer devices and with the exchange computersystem 100. Depending on the type of computer device, a user caninteract with the computer with a keyboard, pointing device, microphone,pen device or other input device now available or later developed.

An exemplary computer device 150 is shown directly connected to exchangecomputer system 100, such as via a T1 line, a common local area network(LAN) or other wired and/or wireless medium for connecting computerdevices, such as the network 220 shown in FIG. 2 and described withrespect thereto. The exemplary computer device 150 is further shownconnected to a radio 168. The user of radio 168, which may include acellular telephone, smart phone, or other wireless proprietary and/ornon-proprietary device, may be a trader or exchange employee. The radiouser may transmit orders or other information to the exemplary computerdevice 150 or a user thereof. The user of the exemplary computer device150, or the exemplary computer device 150 alone and/or autonomously, maythen transmit the trade or other information to the exchange computersystem 100.

Exemplary computer devices 152 and 154 are coupled with a local areanetwork (“LAN”) 160 which may be configured in one or more of thewell-known LAN topologies, e.g., star, daisy chain, etc., and may use avariety of different protocols, such as Ethernet, TCP/IP, etc. Theexemplary computer devices 152 and 154 may communicate with each otherand with other computer and other devices which are coupled with the LAN160. Computer and other devices may be coupled with the LAN 160 viatwisted pair wires, coaxial cable, fiber optics or other wired orwireless media. As shown in FIG. 1, an exemplary wireless personaldigital assistant device (“PDA”) 158, such as a mobile telephone, tabletbased compute device, or other wireless device, may communicate with theLAN 160 and/or the Internet 162 via radio waves, such as via WIFI,Bluetooth® and/or a cellular telephone based data communicationsprotocol. PDA 158 may also communicate with exchange computer system 100via a conventional wireless hub 164.

FIG. 1 also shows the LAN 160 coupled with a wide area network (“WAN”)162 which may be comprised of one or more public or private wired orwireless networks. In one embodiment, the WAN 162 includes the Internet162. The LAN 160 may include a router to connect LAN 160 to the Internet162. Exemplary computer device 156 is shown coupled directly to theInternet 162, such as via a modem, DSL line, satellite dish or any otherdevice for connecting a computer device to the Internet 162 via aservice provider therefore as is known. LAN 160 and/or WAN 162 may bethe same as the network 220 shown in FIG. 2 and described with respectthereto.

Users of the exchange computer system 100 may include one or more marketmakers 166 which may maintain a market by providing constant bid andoffer prices for a derivative or security to the exchange computersystem 100, such as via one of the exemplary computer devices depicted.The exchange computer system 100 may also exchange information withother match or trade engines, such as trade engine 170. One skilled inthe art will appreciate that numerous additional computers and systemsmay be coupled to exchange computer system 100. Such computers andsystems may include clearing, regulatory and fee systems.

The operations of computer devices and systems shown in FIG. 1 may becontrolled by computer-executable instructions stored on anon-transitory computer-readable medium. For example, the exemplarycomputer device 152 may store computer-executable instructions forreceiving order information from a user, transmitting that orderinformation to exchange computer system 100 in electronic messages,extracting the order information from the electronic messages, executingactions relating to the messages, and/or calculating values fromcharacteristics of the extracted order to facilitate matching orders andexecuting trades. In another example, the exemplary computer device 154may include computer-executable instructions for receiving market datafrom exchange computer system 100 and displaying that information to auser.

Numerous additional servers, computers, handheld devices, personaldigital assistants, telephones, and other devices may also be connectedto exchange computer system 100. Moreover, one skilled in the art willappreciate that the topology shown in FIG. 1 is merely an example andthat the components shown in FIG. 1 may include other components notshown and be connected by numerous alternative topologies.

Referring now to FIG. 2, an illustrative embodiment of a generalcomputer system 200 is shown. The computer system 200 can include a setof instructions that can be executed to cause the computer system 200 toperform any one or more of the methods or computer-based functionsdisclosed herein. The computer system 200 may operate as a standalonedevice or may be connected, e.g., using a network, to other computersystems or peripheral devices. Any of the components discussed herein,such as processor 202, may be a computer system 200 or a component inthe computer system 200. The computer system 200 may be specificallyconfigured to implement a match engine, margin processing, payment orclearing function on behalf of an exchange, such as the ChicagoMercantile Exchange Inc., of which the disclosed embodiments are acomponent thereof.

In a networked deployment, the computer system 200 may operate in thecapacity of a server or as a client user computer in a client-serveruser network environment, or as a peer computer system in a peer-to-peer(or distributed) network environment. The computer system 200 can alsobe implemented as or incorporated into various devices, such as apersonal computer (PC), a tablet PC, a set-top box (STB), a personaldigital assistant (PDA), a mobile device, a palmtop computer, a laptopcomputer, a desktop computer, a communications device, a wirelesstelephone, a land-line telephone, a control system, a camera, a scanner,a facsimile machine, a printer, a pager, a personal trusted device, aweb appliance, a network router, switch or bridge, or any other machinecapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that machine. In a particularembodiment, the computer system 200 can be implemented using electronicdevices that provide voice, video, or data communication. Further, whilea single computer system 200 is illustrated, the term “system” shallalso be taken to include any collection of systems or sub-systems thatindividually or jointly execute a set, or multiple sets, of instructionsto perform one or more computer functions.

As illustrated in FIG. 2, the computer system 200 may include aprocessor 202, e.g., a central processing unit (CPU), a graphicsprocessing unit (GPU), or both. The processor 202 may be a component ina variety of systems. For example, the processor 202 may be part of astandard personal computer or a workstation. The processor 202 may beone or more general processors, digital signal processors, specificallyconfigured processors, application specific integrated circuits, fieldprogrammable gate arrays, servers, networks, digital circuits, analogcircuits, combinations thereof, or other now known or later developeddevices for analyzing and processing data. The processor 202 mayimplement a software program, such as code generated manually (i.e.,programmed).

The computer system 200 may include a memory 204 that can communicatevia a bus 208. The memory 204 may be a main memory, a static memory, ora dynamic memory. The memory 204 may include, but is not limited to,computer readable storage media such as various types of volatile andnon-volatile storage media, including but not limited to random accessmemory, read-only memory, programmable read-only memory, electricallyprogrammable read-only memory, electrically erasable read-only memory,flash memory, magnetic tape or disk, optical media and the like. In oneembodiment, the memory 204 includes a cache or random-access memory forthe processor 202. In alternative embodiments, the memory 204 isseparate from the processor 202, such as a cache memory of a processor,the system memory, or other memory. The memory 204 may be an externalstorage device or database for storing data. Examples include a harddrive, compact disc (“CD”), digital video disc (“DVD”), memory card,memory stick, floppy disc, universal serial bus (“USB”) memory device,or any other device operative to store data. The memory 204 is operableto store instructions executable by the processor 202. The functions,acts or tasks illustrated in the figures or described herein may beperformed by the programmed processor 202 executing the instructions 212stored in the memory 204. The functions, acts or tasks are independentof the particular type of instructions set, storage media, processor orprocessing strategy and may be performed by software, hardware,integrated circuits, firmware, micro-code and the like, operating aloneor in combination. Likewise, processing strategies may includemultiprocessing, multitasking, parallel processing and the like.

As shown, the computer system 200 may further include a display unit214, such as a liquid crystal display (LCD), an organic light emittingdiode (OLED), a flat panel display, a solid state display, a cathode raytube (CRT), a projector, a printer or other now known or later developeddisplay device for outputting determined information. The display 214may act as an interface for the user to see the functioning of theprocessor 202, or specifically as an interface with the software storedin the memory 204 or in the drive unit 206.

Additionally, the computer system 200 may include an input device 216configured to allow a user to interact with any of the components ofsystem 200. The input device 216 may be a number pad, a keyboard, or acursor control device, such as a mouse, or a joystick, touch screendisplay, remote control, or any other device operative to interact withthe system 200.

In a particular embodiment, as depicted in FIG. 2, the computer system200 may also include a disk or optical drive unit 206. The disk driveunit 206 may include a computer-readable medium 210 in which one or moresets of instructions 212, e.g., software, can be embedded. Further, theinstructions 212 may embody one or more of the methods or logic asdescribed herein. In a particular embodiment, the instructions 212 mayreside completely, or at least partially, within the memory 204 and/orwithin the processor 202 during execution by the computer system 200.The memory 204 and the processor 202 also may include computer-readablemedia as discussed herein.

The present disclosure contemplates a computer-readable medium thatincludes instructions 212 or receives and executes instructions 212responsive to a propagated signal, so that a device connected to anetwork 220 can communicate voice, video, audio, images, or any otherdata over the network 220. Further, the instructions 212 may betransmitted or received over the network 220 via a communicationinterface 218. The communication interface 218 may be a part of theprocessor 202 or may be a separate component. The communicationinterface 218 may be created in software or may be a physical connectionin hardware. The communication interface 218 is configured to connectwith a network 220, external media, the display 214, or any othercomponents in system 200, or combinations thereof. The connection withthe network 220 may be a physical connection, such as a wired Ethernetconnection or may be established wirelessly. Likewise, the additionalconnections with other components of the system 200 may be physicalconnections or may be established wirelessly.

The network 220 may include wired networks, wireless networks, orcombinations thereof. The wireless network may be a cellular telephonenetwork, an 802.11, 802.16, 802.20, or WiMAX network. Further, thenetwork 220 may be a public network, such as the Internet, a privatenetwork, such as an intranet, or combinations thereof, and may utilize avariety of networking protocols now available or later developedincluding, but not limited to, TCP/IP based networking protocols.

Embodiments of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, or in computer software, firmware, or hardware, including thestructures disclosed in this specification and their structuralequivalents, or in combinations of one or more of them. Embodiments ofthe subject matter described in this specification can be implemented asone or more computer program products, i.e., one or more modules ofcomputer program instructions encoded on a computer readable medium forexecution by, or to control the operation of, data processing apparatus.While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any medium that is capableof storing, encoding, or carrying a set of instructions for execution bya processor or that cause a computer system to perform any one or moreof the methods or operations disclosed herein. The computer readablemedium can be a machine-readable storage device, a machine-readablestorage substrate, a memory device, or a combination of one or more ofthem. The term “data processing apparatus” encompasses all apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, or multiple processors or computers.The apparatus can include, in addition to hardware, code that creates anexecution environment for the computer program in question, e.g., codethat constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, or a combination of one or moreof them.

In a particular non-limiting, exemplary embodiment, thecomputer-readable medium can include a solid-state memory such as amemory card or other package that houses one or more non-volatileread-only memories. Further, the computer-readable medium can be arandom-access memory or other volatile re-writable memory. Additionally,the computer-readable medium can include a magneto-optical or opticalmedium, such as a disk or tapes or other storage device to capturecarrier wave signals such as a signal communicated over a transmissionmedium. A digital file attachment to an e-mail or other self-containedinformation archive or set of archives may be considered a distributionmedium that is a tangible storage medium. Accordingly, the disclosure isconsidered to include any one or more of a computer-readable medium or adistribution medium and other equivalents and successor media, in whichdata or instructions may be stored.

In an alternative embodiment, dedicated or otherwise specificallyconfigured hardware implementations, such as application specificintegrated circuits, programmable logic arrays and other hardwaredevices, can be constructed to implement one or more of the methodsdescribed herein. Applications that may include the apparatus andsystems of various embodiments can broadly include a variety ofelectronic and computer systems. One or more embodiments describedherein may implement functions using two or more specific interconnectedhardware modules or devices with related control and data signals thatcan be communicated between and through the modules, or as portions ofan application-specific integrated circuit. Accordingly, the presentsystem encompasses software, firmware, and hardware implementations.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented by software programsexecutable by a computer system. Further, in an exemplary, non-limitedembodiment, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionalities as describedherein.

Although the present specification describes components and functionsthat may be implemented in particular embodiments with reference toparticular standards and protocols, the invention is not limited to suchstandards and protocols. For example, standards for Internet and otherpacket switched network transmission (e.g., TCP/IP, UDP/IP, HTML, HTTP,HTTPS) represent examples of the state of the art. Such standards areperiodically superseded by faster or more efficient equivalents havingessentially the same functions. Accordingly, replacement standards andprotocols having the same or similar functions as those disclosed hereinare considered equivalents thereof.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a standalone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andanyone or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random-access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Moreover, a computer can be embedded inanother device, e.g., a mobile telephone, a personal digital assistant(PDA), a mobile audio player, a Global Positioning System (GPS)receiver, to name just a few. Computer readable media suitable forstoring computer program instructions and data include all forms ofnon-volatile memory, media and memory devices, including by way ofexample semiconductor memory devices, e.g., EPROM, EEPROM, and flashmemory devices; magnetic disks, e.g., internal hard disks or removabledisks; magneto optical disks; and CD ROM and DVD-ROM discs. Theprocessor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

As used herein, the terms “microprocessor” or “general-purposeprocessor” (“GPP”) may refer to a hardware device that fetchesinstructions and data from a memory or storage device and executes thoseinstructions (for example, an Intel Xeon processor or an AMD Opteronprocessor) to then, for example, process the data in accordancetherewith. The term “reconfigurable logic” may refer to any logictechnology whose form and function can be significantly altered (i.e.,reconfigured) in the field post-manufacture as opposed to amicroprocessor, whose function can change post-manufacture, e.g. viacomputer executable software code, but whose form, e.g. thearrangement/layout and interconnection of logical structures, is fixedat manufacture. The term “software” may refer to data processingfunctionality that is deployed on a GPP. The term “firmware” may referto data processing functionality that is deployed on reconfigurablelogic. One example of a reconfigurable logic is a field programmablegate array (“FPGA”) which is a reconfigurable integrated circuit. AnFPGA may contain programmable logic components called “logic blocks”,and a hierarchy of reconfigurable interconnects that allow the blocks tobe “wired together”, somewhat like many (changeable) logic gates thatcan be inter-wired in (many) different configurations. Logic blocks maybe configured to perform complex combinatorial functions, or merelysimple logic gates like AND, OR, NOT and XOR. An FPGA may furtherinclude memory elements, which may be simple flip-flops or more completeblocks of memory.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a devicehaving a display, e.g., a CRT (cathode ray tube) or LCD (liquid crystaldisplay) monitor, for displaying information to the user and a keyboardand a pointing device, e.g., a mouse or a trackball, by which the usercan provide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well. Feedback provided to theuser can be any form of sensory feedback, e.g., visual feedback,auditory feedback, or tactile feedback. Input from the user can bereceived in any form, including acoustic, speech, or tactile input.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back end component,e.g., a data server, or that includes a middleware component, e.g., anapplication server, or that includes a front end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back end, middleware, or front end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), e.g., the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

It should be appreciated that the disclosed embodiments may beapplicable to other types of messages depending upon the implementation.Further, the messages may comprise one or more data packets, datagramsor other collection of data formatted, arranged configured and/orpackaged in a particular one or more protocols, e.g., the FIX protocol,TCP/IP, Ethernet, etc., suitable for transmission via a network 214 aswas described, such as the message format and/or protocols described inU.S. Pat. No. 7,831,491 and U.S. Patent Publication No. 2005/0096999 A1,both of which are incorporated by reference herein in their entiretiesand relied upon. Further, the disclosed message management system may beimplemented using an open message standard implementation, such as FIX,FIX Binary, FIX/FAST, or by an exchange-provided API.

The embodiments described herein utilize trade related electronicmessages such as mass quote messages, individual order messages,modification messages, cancellation messages, etc., so as to enacttrading activity in an electronic market. The trading entity and/ormarket participant may have one or multiple trading terminals associatedwith the session. Furthermore, the financial instruments may befinancial derivative products. Derivative products may include futurescontracts, options on futures contracts, futures contracts that arefunctions of or related to other futures contracts, swaps, swaptions, orother financial instruments that have their price related to or derivedfrom an underlying product, security, commodity, equity, index, orinterest rate product. In one embodiment, the orders are for optionscontracts that belong to a common option class. Orders may also be forbaskets, quadrants, other combinations of financial instruments, etc.The option contracts may have a plurality of strike prices and/orcomprise put and call contracts. A mass quote message may be received atan exchange. As used herein, an exchange computing system 100 includes aplace or system that receives and/or executes orders.

In an embodiment, a plurality of electronic messages is received fromthe network. The plurality of electronic messages may be received at anetwork interface for the electronic trading system. The plurality ofelectronic messages may be sent from market participants. The pluralityof messages may include order characteristics and be associated withactions to be executed with respect to an order that may be extractedfrom the order characteristics. The action may involve any action asassociated with transacting the order in an electronic trading system.The actions may involve placing the orders within a particular marketand/or order book of a market in the electronic trading system.

The electronic messages may also include other data relating to theorder. In an embodiment, the other data may be data indicating aparticular time in which the action is to be executed. As such, theorder may be considered a temporally specific order. The particular timein which an action is undertaken may be established with respect to anymeasure of absolute or relative time.

In an embodiment, the electronic message may also include other actionsto be taken with respect to the order. These other actions may beactions to be executed after the initial or primary action associatedwith the order. For example, the actions may involve modifying orcanceling an already placed order. Further, in an embodiment, the otherdata may indicate order modification characteristics. For example, theother data may include a price or volume change in an order. The otheractions may involve modifying the already placed order to align with theorder modification characteristics, such as changing the price or volumeof the already placed order.

In an embodiment, other actions may be dependent actions. For example,the execution of the actions may involve a detection of an occurrence ofan event. Such triggering events may be described as other data in theelectronic message. For example, the triggering event may be a releaseof an economic statistic from an organization relating to a productbeing bought or sold in the electronic market, a receipt of pricinginformation from a correlated electronic market, a detection of a changein market sentiment derived from identification of keywords in socialmedia or public statements of officials related to a product beingbought or sold in the electronic market, and/or any other event orcombination of events which may be detected by an electronic tradingsystem.

In an embodiment, the action, or a primary action, associated with anorder may be executed. For example, an order extracted from electronicmessage order characteristics may be placed into a market, or anelectronic order book for a market, such that the order may be matchedwith other orders counter thereto.

In an embodiment, messages received prior to the beginning time but nothaving a particular time specified will have the associated actionexecuted as soon as possible after the beginning time. Because of this,specifying a time for order action execution may allow a distributionand more definite relative time of order placement so as to allowresources of the electronic trading system to operate more efficiently.

The electronic trading system may distribute the ability to submittemporally specific message to selected market participants. Forexample, only five temporally specific messages may be allowed in anyone particular period or sub-period. Further, the ability to submittemporally specific messages within particular periods or sub-periodsmay be distributed based on any technique. For example, the temporallyspecific messages for a particular sub-period may be auctioned off orotherwise sold by the electronic trading system to market participants.Also, the electronic trading system may distribute the temporallyspecific messages to preferred market participants, or as an incentiveto participate in a particular market.

In an embodiment, an event occurrence may be detected. The eventoccurrence may be the occurrence of an event that was specified as otherinformation relating to an order extracted from an electronic message.The event may be a triggering event for a modification or cancellationaction associated with an order. The event may be detected subsequent tothe execution of the first action when an electronic message furthercomprises the data representative of the event and a secondary actionassociated with the order.

In an embodiment, other actions associated with an order may beexecuted. The other actions may be any action associated with an order.For example, the action may be a conditional action that is executed inresponse to a detection of an occurrence of an event.

An event may be a release of an economic statistic or a fluctuation ofprices in a correlated market. An event may also be a perceptible changein market sentiment of a correlated market. A change may be perceptiblebased on a monitoring of orders or social media for keywords inreference to the market in question. For example, electronic tradingsystems may be configured to be triggered for action by a use ofkeywords during a course of ongoing public statements of officials whomay be in a position to impact markets, such as Congressional testimonyof the Chairperson of the Federal Reserve System.

The other or secondary action may also be considered a modification of afirst action executed with respect to an order. For example, acancellation may be considered a cancellation of the placement of theorder. Further, a secondary action may have other data in the messagewhich indicates a specific time in which the secondary action may beexecuted. The specific time may be a time relative to a first action, orplacement of the order. Further, multiple secondary actions may beprovided for a single order. Also, with each secondary action adifferent triggering event may be provided.

In an embodiment, an incoming transaction may be received. The incomingtransaction may be from, and therefore associated with, a marketparticipant of an electronic market managed by an electronic tradingsystem. The transaction may involve an order as extracted from areceived message and may have an associated action. The actions mayinvolve placing an order to buy or sell a financial product in theelectronic market or modifying or deleting such an order. In anembodiment, the financial product may be based on an associatedfinancial instrument which the electronic market is established totrade.

In an embodiment, the action associated with the transaction isdetermined. For example, it may be determined whether the incomingtransaction comprises an order to buy or sell a quantity of theassociated financial instrument or an order to modify or cancel anexisting order in the electronic market. Orders to buy or sell andorders to modify or cancel may be acted upon differently by theelectronic market. For example, data indicative of differentcharacteristics of the types of orders may be stored.

In an embodiment, data relating to the received transaction is stored.The data may be stored in any device, or using any technique, operableto store and provide recovery of data. For example, a memory 204 orcomputer readable medium 210, may be used to store data, as is describedwith respect to FIG. 2 in further detail herein. Data may be storedrelating received transactions for a period of time, indefinitely, orfor a rolling most recent time period such that the stored data isindicative of the market participant's recent activity in the electronicmarket.

If and/or when a transaction is determined to be an order to modify orcancel a previously placed, or existing, order, data indicative of theseactions may be stored. For example, data indicative of a running countof a number or frequency of the receipt of modify or cancel orders fromthe market participant may be stored. A number may be a total number ofmodify or cancel orders received from the market participant, or anumber of modify or cancel orders received from the market participantover a specified time. A frequency may be a time based frequency, as ina number of cancel or modify orders per unit of time, or a number ofcancel or modify orders received from the market participant as apercentage of total transactions received from the participant, whichmay or may not be limited by a specified length of time.

If and/or when a transaction is determined to be an order to buy or sella financial product, or financial instrument, other indicative data maybe stored. For example, data indicative of quantity and associated priceof the order to buy or sell may be stored.

Data indicative of attempts to match incoming orders may also be stored.The data may be stored in any device, or using any technique, operableto store and provide recovery of data. For example, a memory 204 orcomputer readable medium 210, may be used to store data, as is describedwith respect to FIG. 2. The acts of the process as described herein mayalso be repeated. As such, data for multiple received transactions formultiple market participants may be stored and used as describe herein.

The order processing module 118 may also store data indicative ofcharacteristics of the extracted orders. For example, the orderprocessing module may store data indicative of orders having anassociated modify or cancel action, such as by recording a count of thenumber of such orders associated with particular market participants.The order processing module may also store data indicative of quantitiesand associated prices of orders to buy or sell a product placed in themarket order book 110, as associated with particular marketparticipants.

Also, the order processing module 118 may be configured to calculate andassociate with particular orders a value indicative of an associatedmarket participant's market activity quality, which is a valueindicative of whether the market participant's market activity increasesor tends to increase liquidity of a market. This value may be determinedbased on the price of the particular order, previously stored quantitiesof orders from the associated market participant, the previously storeddata indicative of previously received orders to modify or cancel asassociated with the market participant, and previously stored dataindicative of a result of the attempt to match previously receivedorders stored in association with the market participant. The orderprocessing module 118 may determine or otherwise calculate scoresindicative of the quality value based on these stored extracted ordercharacteristics, such as an MQI as described herein.

Further, electronic trading systems may perform actions on orders placedfrom received messages based on various characteristics of the messagesand/or market participants associated with the messages. These actionsmay include matching the orders either during a continuous auctionprocess. The matching of orders may be by any technique.

The matching of orders may occur based on a priority indicated by thecharacteristics of orders and market participants associated with theorders. Orders having a higher priority may be matched before orders ofa lower priority. Such priority may be determined using varioustechniques. For example, orders that were indicated by messages receivedearlier may receive a higher priority to match than orders that wereindicated by messages received later. Also, scoring or grading of thecharacteristics may provide for priority determination. Data indicativeof order matches may be stored by a match engine and/or an orderprocessing module 118 and used for determining MQI scores of marketparticipants.

Example Users

Generally, a market may involve market makers, such as marketparticipants who consistently provide bids and/or offers at specificprices in a manner typically conducive to balancing risk, and markettakers who may be willing to execute transactions at prevailing bids oroffers may be characterized by more aggressive actions so as to maintainrisk and/or exposure as a speculative investment strategy. From analternate perspective, a market maker may be considered a marketparticipant who places an order to sell at a price at which there is nopreviously or concurrently provided counter order. Similarly, a markettaker may be considered a market participant who places an order to buyat a price at which there is a previously or concurrently providedcounter order. A balanced and efficient market may involve both marketmakers and market takers, coexisting in a mutually beneficial basis. Themutual existence, when functioning properly, may facilitate liquidity inthe market such that a market may exist with “tight” bid-ask spreads(e.g., small difference between bid and ask prices) and a “deep” volumefrom many currently provided orders such that large quantity orders maybe executed without driving prices significantly higher or lower.

As such, both market participant types are useful in generatingliquidity in a market, but specific characteristics of market activitytaken by market participants may provide an indication of a particularmarket participant's effect on market liquidity. For example, a MarketQuality Index (“MQI”) of an order may be determined using thecharacteristics. An MQI may be considered a value indicating alikelihood that a particular order will improve or facilitate liquidityin a market. That is, the value may indicate a likelihood that the orderwill increase a probability that subsequent requests and transactionfrom other market participants will be satisfied. As such, an MQI may bedetermined based on a proximity of the entered price of an order to amidpoint of a current bid-ask price spread, a size of the entered order,a volume or quantity of previously filled orders of the marketparticipant associated with the order, and/or a frequency ofmodifications to previous orders of the market participant associatedwith the order. In this way, an electronic trading system may functionto assess and/or assign an MQI to received electronic messages toestablish messages that have a higher value to the system, and thus thesystem may use computing resources more efficiently by expendingresources to match orders of the higher value messages prior toexpending resources of lower value messages.

While an MQI may be applied to any or all market participants, such anindex may also be applied only to a subset thereof, such as large marketparticipants, or market participants whose market activity as measuredin terms of average daily message traffic over a limited historical timeperiod exceeds a specified number. For example, a market participantgenerating more than 500, 1,000, or even 10,000 market messages per daymay be considered a large market participant.

An exchange provides one or more markets for the purchase and sale ofvarious types of products including financial instruments such asstocks, bonds, futures contracts, options, currency, cash, and othersimilar instruments. Agricultural products and commodities are alsoexamples of products traded on such exchanges. A futures contract is aproduct that is a contract for the future delivery of another financialinstrument such as a quantity of grains, metals, oils, bonds, currency,or cash. Generally, each exchange establishes a specification for eachmarket provided thereby that defines at least the product traded in themarket, minimum quantities that must be traded, and minimum changes inprice (e.g., tick size). For some types of products (e.g., futures oroptions), the specification further defines a quantity of the underlyingproduct represented by one unit (or lot) of the product, and deliveryand expiration dates. As will be described, the exchange may furtherdefine the matching algorithm, or rules, by which incoming orders willbe matched/allocated to resting orders.

Matching and Transaction Processing

Market participants, e.g., traders, use software to send orders ormessages to the trading platform. The order identifies the product, thequantity of the product the trader wishes to trade, a price at which thetrader wishes to trade the product, and a direction of the order (i.e.,whether the order is a bid, i.e., an offer to buy, or an ask, i.e., anoffer to sell). It will be appreciated that there may be other ordertypes or messages that traders can send including requests to modify orcancel a previously submitted order.

The exchange computer system monitors incoming orders received therebyand attempts to identify, i.e., match or allocate, as described herein,one or more previously received, but not yet matched, orders, i.e.,limit orders to buy or sell a given quantity at a given price, referredto as “resting” orders, stored in an order book database, wherein eachidentified order is contra to the incoming order and has a favorableprice relative to the incoming order. An incoming order may be an“aggressor” order, i.e., a market order to sell a given quantity atwhatever may be the current resting bid order price(s) or a market orderto buy a given quantity at whatever may be the current resting ask orderprice(s). An incoming order may be a “market making” order, i.e., amarket order to buy or sell at a price for which there are currently noresting orders. In particular, if the incoming order is a bid, i.e., anoffer to buy, then the identified order(s) will be an ask, i.e., anoffer to sell, at a price that is identical to or higher than the bidprice. Similarly, if the incoming order is an ask, i.e., an offer tosell, the identified order(s) will be a bid, i.e., an offer to buy, at aprice that is identical to or lower than the offer price.

An exchange computing system may receive conditional orders or messagesfor a data object, where the order may include two prices or values: areference value and a stop value. A conditional order may be configuredso that when a product represented by the data object trades at thereference price, the stop order is activated at the stop value. Forexample, if the exchange computing system's order management moduleincludes a stop order with a stop price of 5 and a limit price of 1 fora product, and a trade at 5 (i.e., the stop price of the stop order)occurs, then the exchange computing system attempts to trade at 1 (i.e.,the limit price of the stop order). In other words, a stop order is aconditional order to trade (or execute) at the limit price that istriggered (or elected) when a trade at the stop price occurs.

Stop orders also rest on, or are maintained in, an order book to monitorfor a trade at the stop price, which triggers an attempted trade at thelimit price. In some embodiments, a triggered limit price for a stoporder may be treated as an incoming order.

Upon identification (matching) of a contra order(s), a minimum of thequantities associated with the identified order and the incoming orderis matched and that quantity of each of the identified and incomingorders become two halves of a matched trade that is sent to a clearinghouse. The exchange computer system considers each identified order inthis manner until either all of the identified orders have beenconsidered or all of the quantity associated with the incoming order hasbeen matched, i.e., the order has been filled. If any quantity of theincoming order remains, an entry may be created in the order bookdatabase and information regarding the incoming order is recordedtherein, i.e., a resting order is placed on the order book for theremaining quantity to await a subsequent incoming order counter thereto.

It should be appreciated that in electronic trading systems implementedvia an exchange computing system, a trade price (or match value) maydiffer from (i.e., be better for the submitter, e.g., lower than asubmitted buy price or higher than a submitted sell price) the limitprice that is submitted, e.g., a price included in an incoming message,or a triggered limit price from a stop order.

As used herein, “better” than a reference value means lower than thereference value if the transaction is a purchase (or acquire)transaction, and higher than the reference value if the transaction is asell transaction. Said another way, for purchase (or acquire)transactions, lower values are better, and for relinquish or selltransactions, higher values are better.

Traders access the markets on a trading platform using trading softwarethat receives and displays at least a portion of the order book for amarket, i.e., at least a portion of the currently resting orders,enables a trader to provide parameters for an order for the producttraded in the market, and transmits the order to the exchange computersystem. The trading software typically includes a graphical userinterface to display at least a price and quantity of some of theentries in the order book associated with the market. The number ofentries of the order book displayed is generally preconfigured by thetrading software, limited by the exchange computer system, or customizedby the user. Some graphical user interfaces display order books ofmultiple markets of one or more trading platforms. The trader may be anindividual who trades on his/her behalf, a broker trading on behalf ofanother person or entity, a group, or an entity. Furthermore, the tradermay be a system that automatically generates and submits orders.

If the exchange computer system identifies that an incoming market ordermay be filled by a combination of multiple resting orders, e.g., theresting order at the best price only partially fills the incoming order,the exchange computer system may allocate the remaining quantity of theincoming, i.e., that which was not filled by the resting order at thebest price, among such identified orders in accordance withprioritization and allocation rules/algorithms, referred to as“allocation algorithms” or “matching algorithms,” as, for example, maybe defined in the specification of the particular financial product ordefined by the exchange for multiple financial products. Similarly, ifthe exchange computer system identifies multiple orders contra to theincoming limit order and that have an identical price which is favorableto the price of the incoming order, i.e., the price is equal to orbetter, e.g., lower if the incoming order is a buy (or instruction topurchase, or instruction to acquire) or higher if the incoming order isa sell (or instruction to relinquish), than the price of the incomingorder, the exchange computer system may allocate the quantity of theincoming order among such identified orders in accordance with thematching algorithms as, for example, may be defined in the specificationof the particular financial product or defined by the exchange formultiple financial products.

An exchange responds to inputs, such as trader orders, cancellation,etc., in a manner as expected by the market participants, such as basedon market data, e.g., prices, available counter-orders, etc., to providean expected level of certainty that transactions will occur in aconsistent and predictable manner and without unknown or unascertainablerisks. Accordingly, the method by which incoming orders are matched withresting orders must be defined so that market participants have anexpectation of what the result will be when they place an order or haveresting orders and an incoming order is received, even if the expectedresult is, in fact, at least partially unpredictable due to somecomponent of the process being random or arbitrary or due to marketparticipants having imperfect or less than all information, e.g.,unknown position of an order in an order book. Typically, the exchangedefines the matching/allocation algorithm that will be used for aparticular financial product, with or without input from the marketparticipants. Once defined for a particular product, thematching/allocation algorithm is typically not altered, except inlimited circumstance, such as to correct errors or improve operation, soas not to disrupt trader expectations. It will be appreciated thatdifferent products offered by a particular exchange may use differentmatching algorithms.

For example, a first-in/first-out (FIFO) matching algorithm, alsoreferred to as a “Price Time” algorithm, considers each identified ordersequentially in accordance with when the identified order was received.The quantity of the incoming order is matched to the quantity of theidentified order at the best price received earliest, then quantities ofthe next earliest best price orders, and so on until the quantity of theincoming order is exhausted. Some product specifications define the useof a pro-rata matching algorithm, wherein a quantity of an incomingorder is allocated to each of plurality of identified ordersproportionally. Some exchange computer systems provide a priority tocertain standing orders in particular markets. An example of such anorder is the first order that improves a price (i.e., improves themarket) for the product during a trading session. To be given priority,the trading platform may require that the quantity associated with theorder is at least a minimum quantity. Further, some exchange computersystems cap the quantity of an incoming order that is allocated to astanding order on the basis of a priority for certain markets. Inaddition, some exchange computer systems may give a preference to orderssubmitted by a trader who is designated as a market maker for theproduct. Other exchange computer systems may use other criteria todetermine whether orders submitted by a particular trader are given apreference. Typically, when the exchange computer system allocates aquantity of an incoming order to a plurality of identified orders at thesame price, the trading host allocates a quantity of the incoming orderto any orders that have been given priority. The exchange computersystem thereafter allocates any remaining quantity of the incoming orderto orders submitted by traders designated to have a preference, and thenallocates any still remaining quantity of the incoming order using theFIFO or pro-rata algorithms. Pro-rata algorithms used in some marketsmay require that an allocation provided to a particular order inaccordance with the pro-rata algorithm must meet at least a minimumallocation quantity. Any orders that do not meet or exceed the minimumallocation quantity are allocated to on a FIFO basis after the pro-rataallocation (if any quantity of the incoming order remains). Moreinformation regarding order allocation may be found in U.S. Pat. No.7,853,499, the entirety of which is incorporated by reference herein andrelied upon.

Other examples of matching algorithms which may be defined forallocation of orders of a particular financial product include: PriceExplicit Time; Order Level Pro Rata; Order Level Priority Pro Rata;Preference Price Explicit Time; Preference Order Level Pro Rata;Preference Order Level Priority Pro Rata; Threshold Pro-Rata; PriorityThreshold Pro-Rata; Preference Threshold Pro-Rata; Priority PreferenceThreshold Pro-Rata; and Split Price-Time Pro-Rata.

For example, the Price Explicit Time trading policy is based on thebasic Price Time trading policy with Explicit Orders having priorityover Implied Orders at the same price level. The order of traded volumeallocation at a single price level may therefore be: Explicit order witholdest timestamp first; followed by any remaining explicit orders intimestamp sequence (First In, First Out—FIFO) next; followed by impliedorder with oldest timestamp next; followed by any remaining impliedorders in timestamp sequence (FIFO).

In Order Level Pro Rata, also referred to as Price Pro Rata, priority isgiven to orders at the best price (highest for a bid, lowest for anoffer). If there are several orders at this best price, equal priorityis given to every order at this price and incoming business is dividedamong these orders in proportion to their order size. The Pro Ratasequence of events is: 1. Extract all potential matching orders at bestprice from the order book into a list. 2. Sort the list by order size,largest order size first. If equal order sizes, oldest timestamp first.This is the matching list. 3. Find the ‘Matching order size, which isthe total size of all the orders in the matching list. 4. Find the‘tradable volume’, which is the smallest of the matching volume and thevolume left to trade on the incoming order. 5. Allocate volume to eachorder in the matching list in turn, starting at the beginning of thelist. If all the tradable volume gets used up, orders near the end ofthe list may not get allocation. 6. The amount of volume to allocate toeach order is given by the formula: (Order volume/Matchingvolume)*Tradable volume. The result is rounded down (for example,21.99999999 becomes 21) unless the result is less than 1, when itbecomes 1.7. If tradable volume remains when the last order in the listhad been allocated to, return to step 3. Note: The matching list is notre-sorted, even though the volume has changed. The order whichoriginally had the largest volume is still at the beginning of the list.8. If there is still volume left to trade on the incoming order, repeatthe entire algorithm at the next price level.

Order Level Priority Pro Rata, also referred to as Threshold Pro Rata,is similar to the Price (or ‘Vanilla’) Pro Rata algorithm but has avolume threshold defined. Any pro rata allocation below the thresholdwill be rounded down to 0. The initial pass of volume allocation iscarried out in using pro rata; the second pass of volume allocation iscarried out using Price Explicit Time. The Threshold Pro Rata sequenceof events is: 1. Extract all potential matching orders at best pricefrom the order book into a list. 2. Sort the list by explicit timepriority, oldest timestamp first. This is the matching list. 3. Find the‘Matching volume’, which is the total volume of all the orders in thematching list. 4. Find the ‘tradable volume’, which is the smallest ofthe matching volume and the volume left to trade on the incoming order.5. Allocate volume to each order in the matching list in turn, startingat the beginning of the list. 6. The amount of volume to allocate toeach order is given by the formula: (Order volume/Matchingvolume)*Tradable volume. The result is rounded down to the nearest lot(for example, 21.99999999 becomes 21) unless the result is less than thedefined threshold in which case it is rounded down to 0.7. If tradablevolume remains when the last order in the list had been allocated to,the remaining volume is allocated in time priority to the matching list.8. If there is still volume left to trade on the incoming order, repeatthe entire algorithm at the next price level.

In the Split Price Time Pro-Rata algorithms, a Price Time Percentageparameter is defined. This percentage of the matching volume at eachprice is allocated by the Price Explicit Time algorithm and theremainder is allocated by the Threshold Pro-Rata algorithm. There arefour variants of this algorithm, with and without Priority and/orPreference. The Price Time Percentage parameter is an integer between 1and 99. (A percentage of zero would be equivalent to using therespective existing Threshold Pro-Rata algorithm, and a percentage of100 would be equivalent to using the respective existing Price Timealgorithm). The Price Time Volume will be the residual incoming volume,after any priority and/or Preference allocation has been made,multiplied by the Price Time Percentage. Fractional parts will berounded up, so the Price Time Volume will always be at least 1 lot andmay be the entire incoming volume. The Price Time Volume is allocated toresting orders in strict time priority. Any remaining incoming volumeafter the Price Time Volume has been allocated will be allocatedaccording to the respective Threshold Pro-Rata algorithm. The sequenceof allocation, at each price level, is therefore: 1. Priority order, ifapplicable. 2. Preference allocation, if applicable. 3. Price Timeallocation of the configured percentage of incoming volume. 4. ThresholdPro-Rata allocation of any remaining incoming volume. 5. Finalallocation of any leftover lots in time sequence. Any resting order mayreceive multiple allocations from the various stages of the algorithm.

It will be appreciated that there may be other allocation algorithms,including combinations of algorithms, now available or later developed,which may be utilized with the disclosed embodiments, and all suchalgorithms are contemplated herein. In one embodiment, the disclosedembodiments may be used in any combination or sequence with theallocation algorithms described herein.

One exemplary system for matching is described in U.S. patentapplication Ser. No. 13/534,499, filed on Jun. 27, 2012, entitled“Multiple Trade Matching Algorithms,” published as U.S. PatentApplication Publication No. 2014/0006243 A1, the entirety of which isincorporated by reference herein and relied upon, discloses an adaptivematch engine which draws upon different matching algorithms, e.g., therules which dictate how a given order should be allocated amongqualifying resting orders, depending upon market conditions, to improvethe operation of the market. For example, for a financial product, suchas a futures contract, having a future expiration date, the match enginemay match incoming orders according to one algorithm when the remainingtime to expiration is above a threshold, recognizing that during thisportion of the life of the contract, the market for this product islikely to have high volatility. However, as the remaining time toexpiration decreases, volatility may decrease. Accordingly, when theremaining time to expiration falls below the threshold, the match engineswitches to a different match algorithm which may be designed toencourage trading relative to the declining trading volatility. Thereby,by conditionally switching among matching algorithms within the samefinancial product, as will be described, the disclosed match engine mayautomatically adapt to the changing market conditions of a financialproduct, e.g., a limited life product, in a non-preferential manner,maintaining fair order allocation while improving market liquidity,e.g., over the life of the product.

In one implementation, the system may evaluate market conditions on adaily basis and, based thereon, change the matching algorithm betweendaily trading sessions, i.e., when the market is closed, such that whenthe market reopens, a new trading algorithm is in effect for theparticular product. The system may facilitate more frequent changes tothe matching algorithms so as to dynamically adapt to changing marketconditions, e.g., intra-day changes, and even intra-order matchingchanges. It will be further appreciated that hybrid matching algorithms,which match part of an order using one algorithm and another part of theorder using a different algorithm, may also be used.

With respect to incoming orders, some traders, such as automated and/oralgorithmic traders, attempt to respond to market events, such as tocapitalize upon a mispriced resting order or other market inefficiency,as quickly as possible. This may result in penalizing the trader whomakes an errant trade, or whose underlying trading motivations havechanged, and who cannot otherwise modify or cancel their order fasterthan other traders can submit trades there against. It may consideredthat an electronic trading system that rewards the trader who submitstheir order first creates an incentive to either invest substantialcapital in faster trading systems, participate in the marketsubstantially to capitalize on opportunities (aggressor side/lower risktrading) as opposed to creating new opportunities (market making/higherrisk trading), modify existing systems to streamline business logic atthe cost of trade quality, or reduce one's activities and exposure inthe market. The result may be a lesser quality market and/or reducedtransaction volume, and corresponding thereto, reduced fees to theexchange.

With respect to resting orders, allocation/matching suitable restingorders to match against an incoming order can be performed, as describedherein, in many different ways. Generally, it will be appreciated thatallocation/matching algorithms are only needed when the incoming orderquantity is less than the total quantity of the suitable resting ordersas, only in this situation, is it necessary to decide which restingorder(s) will not be fully satisfied, which trader(s) will not get theirorders filled. It can be seen from the above descriptions of thematching/allocation algorithms, that they fall generally into threecategories: time priority/first-in-first-out (“FIFO”), pro rata, or ahybrid of FIFO and pro rata.

FIFO generally rewards the first trader to place an order at aparticular price and maintains this reward indefinitely. So, if a traderis the first to place an order at price X, no matter how long that orderrests and no matter how many orders may follow at the same price, assoon as a suitable incoming order is received, that first trader will bematched first. This “first mover” system may commit other traders topositions in the queue after the first move traders. Furthermore, whileit may be beneficial to give priority to a trader who is first to placean order at a given price because that trader is, in effect, taking arisk, the longer that the trader's order rests, the less beneficial itmay be. For instance, it could deter other traders from adding liquidityto the marketplace at that price because they know the first mover (andpotentially others) already occupies the front of the queue.

With a pro rata allocation, incoming orders are effectively split amongsuitable resting orders. This provides a sense of fairness in thateveryone may get some of their order filled. However, a trader who tooka risk by being first to place an order (a “market turning” order) at aprice may end up having to share an incoming order with a much latersubmitted order. Furthermore, as a pro rata allocation distributes theincoming order according to a proportion based on the resting orderquantities, traders may place orders for large quantities, which theyare willing to trade but may not necessarily want to trade, in order toincrease the proportion of an incoming order that they will receive.This results in an escalation of quantities on the order book andexposes a trader to a risk that someone may trade against one of theseorders and subject the trader to a larger trade than they intended. Inthe typical case, once an incoming order is allocated against theselarge resting orders, the traders subsequently cancel the remainingresting quantity which may frustrate other traders. Accordingly, as FIFOand pro rata both have benefits and problems, exchanges may try to usehybrid allocation/matching algorithms which attempt to balance thesebenefits and problems by combining FIFO and pro rata in some manner.However, hybrid systems define conditions or fixed rules to determinewhen FIFO should be used and when pro rata should be used. For example,a fixed percentage of an incoming order may be allocated using a FIFOmechanism with the remainder being allocated pro rata.

Spread Instruments

Traders trading on an exchange including, for example, exchange computersystem 100, often desire to trade multiple financial instruments incombination. Each component of the combination may be called a leg.Traders can submit orders for individual legs or in some cases cansubmit a single order for multiple financial instruments in anexchange-defined combination. Such orders may be called a strategyorder, a spread order, or a variety of other names.

A spread instrument may involve the simultaneous purchase of onesecurity and sale of a related security, called legs, as a unit. Thelegs of a spread instrument may be options or futures contracts, orcombinations of the two. Trades in spread instruments are executed toyield an overall net position whose value, called the spread, depends onthe difference between the prices of the legs. Spread instruments may betraded in an attempt to profit from the widening or narrowing of thespread, rather than from movement in the prices of the legs directly.Spread instruments are either “bought” or “sold” depending on whetherthe trade will profit from the widening or narrowing of the spread,respectively. An exchange often supports trading of common spreads as aunit rather than as individual legs, thus ensuring simultaneousexecution of the two legs, eliminating the execution risk of one legexecuting but the other failing.

One example of a spread instrument is a calendar spread instrument. Thelegs of a calendar spread instrument differ in delivery date of theunderlier. The leg with the earlier occurring delivery date is oftenreferred to as the lead month contract. A leg with a later occurringdelivery date is often referred to as a deferred month contract. Anotherexample of a spread instrument is a butterfly spread instrument, whichincludes three legs having different delivery dates. The delivery datesof the legs may be equidistant to each other. The counterparty ordersthat are matched against such a combination order may be individual,“outright” orders or may be part of other combination orders.

In other words, an exchange may receive, and hold or let rest on thebooks, outright orders for individual contracts as well as outrightorders for spreads associated with the individual contracts. An outrightorder (for either a contract or for a spread) may include an outrightbid or an outright offer, although some outright orders may bundle manybids or offers into one message (often called a mass quote).

A spread is an order for the price difference between two contracts.This results in the trader holding a long and a short position in two ormore related futures or options on futures contracts, with the objectiveof profiting from a change in the price relationship. A typical spreadproduct includes multiple legs, each of which may include one or moreunderlying financial instruments. A butterfly spread product, forexample, may include three legs. The first leg may consist of buying afirst contract. The second leg may consist of selling two of a secondcontract. The third leg may consist of buying a third contract. Theprice of a butterfly spread product may be calculated as:Butterfly=Leg1−2×Leg2+Leg3  (equation 1)

In the above equation, Leg1 equals the price of the first contract, Leg2equals the price of the second contract and Leg3 equals the price of thethird contract. Thus, a butterfly spread could be assembled from twointer-delivery spreads in opposite directions with the center deliverymonth common to both spreads.

A calendar spread, also called an intra-commodity spread, for futures isan order for the simultaneous purchase and sale of the same futurescontract in different contract months (i.e., buying a September CME S&P500® futures contract and selling a December CME S&P 500 futurescontract).

A crush spread is an order, usually in the soybean futures market, forthe simultaneous purchase of soybean futures and the sale of soybeanmeal and soybean oil futures to establish a processing margin. A crackspread is an order for a specific spread trade involving simultaneouslybuying and selling contracts in crude oil and one or more derivativeproducts, typically gasoline and heating oil. Oil refineries may trade acrack spread to hedge the price risk of their operations, whilespeculators attempt to profit from a change in the oil/gasoline pricedifferential.

A straddle is an order for the purchase or sale of an equal number ofputs and calls, with the same strike price and expiration dates. A longstraddle is a straddle in which a long position is taken in both a putand a call option. A short straddle is a straddle in which a shortposition is taken in both a put and a call option. A strangle is anorder for the purchase of a put and a call, in which the options havethe same expiration and the put strike is lower than the call strike,called a long strangle. A strangle may also be the sale of a put and acall, in which the options have the same expiration and the put strikeis lower than the call strike, called a short strangle. A pack is anorder for the simultaneous purchase or sale of an equally weighted,consecutive series of four futures contracts, quoted on an average netchange basis from the previous day's settlement price. Packs provide areadily available, widely accepted method for executing multiple futurescontracts with a single transaction. A bundle is an order for thesimultaneous sale or purchase of one each of a series of consecutivefutures contracts. Bundles provide a readily available, widely acceptedmethod for executing multiple futures contracts with a singletransaction.

Implication

Thus, an exchange may match outright orders, such as individualcontracts or spread orders (which as discussed herein could includemultiple individual contracts). The exchange may also imply orders fromoutright orders. For example, exchange computer system 100 may derive,identify and/or advertise, publish, display, or otherwise make availablefor trading orders based on outright orders.

As was described above, the financial instruments which are the subjectof the orders to trade, may include one or more component financialinstruments. While each financial instrument may have its own orderbook, i.e. market, in which it may be traded, in the case of a financialinstrument having more than one component financial instrument, thosecomponent financial instruments may further have their own order booksin which they may be traded. Accordingly, when an order for a financialinstrument is received, it may be matched against a suitable counterorder in its own order book or, possibly, against a combination ofsuitable counter orders in the order books the component financialinstruments thereof, or which share a common component financialinstrument. For example, an order for a spread contract comprisingcomponent financial instruments A and B may be matched against anothersuitable order for that spread contract. However, it may also be matchedagainst suitable separate counter orders for the A and for the Bcomponent financial instruments found in the order books, therefore.Similarly, if an order for the A contract is received and suitable matchcannot be found in the A order book, it may be possible to match orderfor A against a combination of a suitable counter order for a spreadcontract comprising the A and B component financial instruments and asuitable counter order for the B component financial instrument. This isreferred to as “implication” where a given order for a financialinstrument may be matched via a combination of suitable counter ordersfor financial instruments which share common, or otherwiseinterdependent, component financial instruments. Implication increasesthe liquidity of the market by providing additional opportunities fororders to be traded. Increasing the number of transactions may furtherincrease the number of transaction fees collected by the electronictrading system.

The order for a particular financial instrument actually received from amarket participant, whether it comprises one or more component financialinstruments, is referred to as a “real” or “outright” order, or simplyas an outright. The one or more orders which must be synthesized andsubmitted into order books other than the order book for the outrightorder in order to create matches therein, are referred to as “implied”orders. Upon receipt of an incoming order, the identification orderivation of suitable implied orders which would allow at least apartial trade of the incoming outright order to be executed is referredto as “implication” or “implied matching”, the identified orders beingreferred to as an “implied match.” Depending on the number componentfinancial instruments involved, and whether those component financialinstruments further comprise component financial instruments of theirown, there may be numerous different implied matches identified whichwould allow the incoming order to be at least partially matched andmechanisms may be provided to arbitrate, e.g., automatically, amongthem, such as by picking the implied match comprising the least numberof component financial instruments or the least number of synthesizedorders.

Upon receipt of an incoming order, or thereafter, a combination of oneor more suitable/hypothetical counter orders which have not actuallybeen received but if they were received, would allow at least a partialtrade of the incoming order to be executed, may be, e.g., automatically,identified or derived and referred to as an “implied opportunity.” Aswith implied matches, there may be numerous implied opportunitiesidentified for a given incoming order. Implied opportunities areadvertised to the market participants, such as via suitable syntheticorders, e.g. counter to the desired order, being placed on therespective order books to rest (or give the appearance that there is anorder resting) and presented via the market data feed, electronicallycommunicated to the market participants, to appear available to trade inorder to solicit the desired orders from the market participants.Depending on the number component financial instruments involved, andwhether those component financial instruments further comprise componentfinancial instruments of their own, there may be numerous impliedopportunities, the submission of a counter order in response thereto,would allow the incoming order to be at least partially matched.

Implied opportunities, e.g. the advertised synthetic orders, mayfrequently have better prices than the corresponding real orders in thesame contract. This can occur when two or more traders incrementallyimprove their order prices in the hope of attracting a trade, sincecombining the small improvements from two or more real orders can resultin a big improvement in their combination. In general, advertisingimplied opportunities at better prices will encourage traders to enterthe opposing orders to trade with them. The more implied opportunitiesthat the match engine of an electronic trading system cancalculate/derive, the greater this encouragement will be and the morethe exchange will benefit from increased transaction volume. However,identifying implied opportunities may be computationally intensive. In ahigh-performance trading system where low transaction latency isimportant, it may be important to identify and advertise impliedopportunities quickly so as to improve or maintain market participantinterest and/or market liquidity.

For example, two different outright orders may be resting on the booksor be available to trade or match. The orders may be resting becausethere are no outright orders that match the resting orders. Thus, eachof the orders may wait or rest on the books until an appropriateoutright counteroffer comes into the exchange or is placed by a user ofthe exchange. The orders may be for two different contracts that onlydiffer in delivery dates. It should be appreciated that such orderscould be represented as a calendar spread order. Instead of waiting fortwo appropriate outright orders to be placed that would match the twoexisting or resting orders, the exchange computer system may identify ahypothetical spread order that, if entered into the system as a tradablespread order, would allow the exchange computer system to match the twooutright orders. The exchange may thus advertise or make available aspread order to users of the exchange system that, if matched with atradable spread order, would allow the exchange to also match the tworesting orders. Thus, the match engine is configured to detect that thetwo resting orders may be combined into an order in the spreadinstrument and accordingly creates an implied order.

In other words, the exchange's matching system may imply thecounteroffer order by using multiple orders to create the counterofferorder. Examples of spreads include implied IN, implied OUT, 2nd- ormultiple-generation, crack spreads, straddle, strangle, butterfly, andpack spreads. Implied IN spread orders are derived from existingoutright orders in individual legs. Implied OUT outright orders arederived from a combination of an existing spread order and an existingoutright order in one of the individual underlying legs. Implied orderscan fill in gaps in the market and allow spreads and outright futurestraders to trade in a product where there would otherwise have beenlittle or no available bids and asks.

For example, implied IN spreads may be created from existing outrightorders in individual contracts where an outright order in a spread canbe matched with other outright orders in the spread or with acombination of orders in the legs of the spread. An implied OUT spreadmay be created from the combination of an existing outright order in aspread and an existing outright order in one of the individualunderlying leg. An implied IN or implied OUT spread may be created whenan electronic match system simultaneously works synthetic spread ordersin spread markets and synthetic orders in the individual leg marketswithout the risk to the trader/broker of being double filled or filledon one leg and not on the other leg.

By linking the spread and outright markets, implied spread tradingincreases market liquidity. For example, a buy in one contract month andan offer in another contract month in the same futures contract cancreate an implied market in the corresponding calendar spread. Anexchange may match an order for a spread product with another order forthe spread product. Some existing exchanges attempt to match orders forspread products with multiple orders for legs of the spread products.With such systems, every spread product contract is broken down into acollection of legs and an attempt is made to match orders for the legs.

Implied orders, unlike real orders, are generated by electronic tradingsystems. In other words, implied orders are computer generated ordersderived from real orders. The system creates the “derived” or “implied”order and provides the implied order as a market that may be tradedagainst. If a trader trades against this implied order, then the realorders that combined to create the implied order and the resultingmarket are executed as matched trades. Implied orders generally increaseoverall market liquidity. The creation of implied orders increases thenumber of tradable items, which has the potential of attractingadditional traders. Exchanges benefit from increased transaction volume.Transaction volume may also increase as the number of matched tradeitems increases.

Examples of implied spread trading include those disclosed in U.S.Patent Publication No. 2005/0203826, entitled “Implied Spread TradingSystem,” the entire disclosure of which is incorporated by referenceherein and relied upon. Examples of implied markets include thosedisclosed in U.S. Pat. No. 7,039,610, entitled “Implied Market TradingSystem,” the entire disclosure of which is incorporated by referenceherein and relied upon.

In some cases, the outright market for the deferred month or otherconstituent contract may not be sufficiently active to provide marketdata (e.g., bid-offer data) and/or trade data. Spread instrumentsinvolving such contracts may nonetheless be made available by theexchange. The market data from the spread instruments may then be usedto determine a settlement price for the constituent contract. Thesettlement price may be determined, for example, through a boundaryconstraint-based technique based on the market data (e.g., bid-offerdata) for the spread instrument, as described in U.S. Patent PublicationNo. 2015/0073962 entitled “Boundary Constraint-Based Settlement inSpread Markets” (“the '962 Publication”), the entire disclosure of whichis incorporated by reference herein and relied upon. Settlement pricedetermination techniques may be implemented to cover calendar monthspread instruments having different deferred month contracts.

Order Book Object Data Structures

In one embodiment, the messages and/or values received for each objectmay be stored in queues according to value and/or priority techniquesimplemented by an exchange computing system 100. FIG. 3A illustrates anexample data structure 300, which may be stored in a memory or otherstorage device, such as the memory 204 or storage device 206 describedwith respect to FIG. 2, for storing and retrieving messages related todifferent values for the same action for an object. For example, datastructure 300 may be a set of queues or linked lists for multiple valuesfor an action, e.g., bid, on an object. Data structure 300 may beimplemented as a database. It should be appreciated that the system maystore multiple values for the same action for an object, for example,because multiple users submitted messages to buy specified quantities ofan object at different values. Thus, in one embodiment, the exchangecomputing system may keep track of different orders or messages forbuying or selling quantities of objects at specified values.

Although the application contemplates using queue data structures forstoring messages in a memory, the implementation may involve additionalpointers, i.e., memory address pointers, or linking to other datastructures. Incoming messages may be stored at an identifiable memoryaddress. The transaction processor can traverse messages in order bypointing to and retrieving different messages from the differentmemories. Thus, messages that may be depicted sequentially, e.g., inFIG. 3B below, may actually be stored in memory in disparate locations.The software programs implementing the transaction processing mayretrieve and process messages in sequence from the various disparate(e.g., random) locations. Thus, in one embodiment, each queue may storedifferent values, which could represent prices, where each value pointsto or is linked to the messages (which may themselves be stored inqueues and sequenced according to priority techniques, such asprioritizing by value) that will match at that value. For example, asshown in FIG. 3A, all of the values relevant to executing an action atdifferent values for an object are stored in a queue. Each value in turnpoints to, e.g., a linked list or queue logically associated with thevalues. The linked list stores the messages that instruct the exchangecomputing system to buy specified quantities of the object at thecorresponding value.

The sequence of the messages in the message queues connected to eachvalue may be determined by exchange implemented priority techniques. Forexample, in FIG. 3A, messages M1, M2, M3 and M4 are associated withperforming an action (e.g., buying or selling) a certain number of units(may be different for each message) at Value 1. M1 has priority over M2,which has priority over M3, which has priority over M4. Thus, if acounter order matches at Value 1, the system fills as much quantity aspossible associated with M1 first, then M2, then M3, and then M4.

In the illustrated examples, the values may be stored in sequentialorder, and the best or lead value for a given queue may be readilyretrievable by and/or accessible to the disclosed system. Thus, in oneembodiment, the value having the best priority may be illustrated asbeing in the topmost position in a queue, although the system may beconfigured to place the best priority message in some otherpredetermined position. In the example of FIG. 3A, Value 1 is shown asbeing the best value or lead value, or the top of the book value, for anexample Action.

FIG. 3B illustrates an example alternative data structure 350 forstoring and retrieving messages and related values. It should beappreciated that matches occur based on values, and so all the messagesrelated to a given value may be prioritized over all other messagesrelated to a different value. As shown in FIG. 3B, the messages may bestored in one queue and grouped by values according to the hierarchy ofthe values. The hierarchy of the values may depend on the action to beperformed.

For example, if a queue is a sell queue (e.g., the Action is Sell), thelowest value may be given the best priority and the highest value may begiven the lowest priority. Thus, as shown in FIG. 3B, if Value 1 islower than Value 2 which is lower than Value 3, Value 1 messages may beprioritized over Value 2, which in turn may be prioritized over Value 3.

Within Value 1, M1 is prioritized over M2, which in turn is prioritizedover M3, which in turn is prioritized over M4. Within Value 2, M5 isprioritized over M6, which in turn is prioritized over M7, which in turnis prioritized over M8. Within Value 3, M9 is prioritized over M10,which in turn is prioritized over M11, which in turn is prioritized overM12.

Alternatively, the messages may be stored in a tree-node data structurethat defines the priorities of the messages. In one embodiment, themessages may make up the nodes.

In one embodiment, the system may traverse through a number of differentvalues and associated messages when processing an incoming message.Traversing values may involve the processor loading each value, checkingthat value, and deciding whether to load another value, i.e., byaccessing the address pointed at by the address pointer value. Inparticular, referring to FIG. 3B, if the queue is for selling an objectfor the listed Values 1, 2 and 3 (where Value 1 is lower than Value 2which is lower than Value 3), and if the system receives an incomingaggressing order to buy quantity X at a Value 4 that is greater thanValues 1, 2, and 3, the system will fill as much of quantity X aspossible by first traversing through the messages under Value 1 (insequence M1, M2, M3, M4). If any of the quantity of X remains, thesystem traverses down the prioritized queue until all of the incomingorder is filled (e.g., all of X is matched) or until all of thequantities of M1 through M12 are filled. Any remaining, unmatchedquantity remains on the books, e.g., as a resting order at Value 4,which was the entered value or the message's value.

The system may traverse the queues and check the values in a queue, andupon finding the appropriate value, may locate the messages involved inmaking that value available to the system. When an outright messagevalue is stored in a queue, and when that outright message is involvedin a trade or match, the system may check the queue for the value, andthen may check the data structure storing messages associated with thatvalue.

In one embodiment, an exchange computing system may convert allfinancial instruments to objects. In one embodiment, an object mayrepresent the order book for a financial instrument. Moreover, in oneembodiment, an object may be defined by two queues, one queue for eachaction that can be performed by a user on the object. For example, anorder book converted to an object may be represented by an Ask queue anda Bid queue. Resting messages or orders associated with the respectivefinancial instrument may be stored in the appropriate queue and recalledtherefrom.

In one embodiment, the messages associated with objects may be stored inspecific ways depending on the characteristics of the various messagesand the states of the various objects in memory. For example, a systemmay hold certain resting messages in queue until the message is to beprocessed, e.g., the message is involved in a match. The order, sequenceor priority given to messages may depend on the characteristics of themessage. For example, in certain environments, messages may indicate anaction that a computer in the system should perform. Actions may becomplementary actions or require more than one message to complete. Forexample, a system may be tasked with matching messages or actionscontained within messages. The messages that are not matched may bequeued by the system in a data queue or other structure, e.g., a datatree having nodes representing messages or orders.

The queues are structured so that the messages are stored in sequenceaccording to priority. Although the embodiments are disclosed as beingimplemented in queues, it should be understood that different datastructures such as for example linked lists or trees may also be used.

The system may include separate data structures, e.g., queues, fordifferent actions associated with different objects within the system.For example, in one embodiment, the system may include a queue for eachpossible action that can be performed on an object. The action may beassociated with a value. The system prioritizes the actions based inpart on the associated value.

For example, as shown in FIG. 3C, the order book module of a computingsystem may include several paired queues, such as queues Bid and Ask foran object 302 (e.g., Object A). The system may include two queues, orone pair of queues, for each object that is matched or processed by thesystem. In one embodiment, the system stores messages in the queues thathave not yet been matched or processed. FIG. 3C may be an implementationof the data structures disclosed in FIGS. 3A and/or 3B. Each queue mayhave a top of book, or lead, position, such as positions 304 and 306,which stores data that is retrievable.

The queues may define the priority or sequence in which messages areprocessed upon a match event. For example, two messages stored in aqueue may represent performing the same action at the same value. When athird message is received by the system that represents a matchingaction at the same value, the system may need to select one of the twowaiting, or resting, messages as the message to use for a match. Thus,when multiple messages can be matched at the same value, the exchangemay have a choice or some flexibility regarding the message that ismatched. The queues may define the priority in which orders that areotherwise equivalent (e.g., same action for the same object at the samevalue) are processed.

The system may include a pair of queues for each object, e.g., a bid andask queue for each object. Each queue may be for example implementedutilizing the data structure of FIG. 3B. The exchange may be able tospecify the conditions upon which a message for an object should beplaced in a queue. For example, the system may include one queue foreach possible action that can be performed on an object. The system maybe configured to process messages that match with each other. In oneembodiment, a message that indicates performing an action at a value maymatch with a message indicating performing a corresponding action at thesame value. Or, the system may determine the existence of a match whenmessages for the same value exist in both queues of the same object.

The messages may be received from the same or different users ortraders.

The queues illustrated in FIG. 3C hold or store messages received by acomputing exchange, e.g., messages submitted by a user to the computingexchange, and waiting for a proper match. It should be appreciated thatthe queues may also hold or store implieds, e.g., implied messagesgenerated by the exchange system, such as messages implied in or impliedout as described herein. The system thus adds messages to the queues asthey are received, e.g., messages submitted by users, or generated,e.g., implied messages generated by the exchanges. The sequence orprioritization of messages in the queues is based on information aboutthe messages and the overall state of the various objects in the system.

When the data transaction processing system is implemented as anexchange computing system, as discussed above, different clientcomputers submit electronic data transaction request messages to theexchange computing system. Electronic data transaction request messagesinclude requests to perform a transaction on a data object, e.g., at avalue for a quantity. The exchange computing system includes atransaction processor, e.g., a hardware matching processor or matchengine, that matches, or attempts to match, pairs of messages with eachother. For example, messages may match if they contain counterinstructions (e.g., one message includes instructions to buy, the othermessage includes instructions to sell) for the same product at the samevalue. In some cases, depending on the nature of the message, the valueat which a match occurs may be the submitted value or a better value. Abetter value may mean higher or lower value depending on the specifictransaction requested. For example, a buy order may match at thesubmitted buy value or a lower (e.g., better) value. A sell order maymatch at the submitted sell value or a higher (e.g., better) value.

Transaction Processor Data Structures

FIG. 4 illustrates an example embodiment of a data structure used toimplement match engine module 106. Match engine module 106 may include aconversion component 402, pre-match queue 404, match component 406,post-match queue 408 and publish component 410.

Although the embodiments are disclosed as being implemented in queues,it should be understood that different data structures, such as forexample linked lists or trees, may also be used. Although theapplication contemplates using queue data structures for storingmessages in a memory, the implementation may involve additionalpointers, i.e., memory address pointers, or linking to other datastructures. Thus, in one embodiment, each incoming message may be storedat an identifiable memory address. The transaction processing componentscan traverse messages in order by pointing to and retrieving differentmessages from the different memories. Thus, messages that may beprocessed sequentially in queues may actually be stored in memory indisparate locations. The software programs implementing the transactionprocessing may retrieve and process messages in sequence from thevarious disparate (e.g., random) locations.

The queues described herein may, in one embodiment, be structured sothat the messages are stored in sequence according to time of receipt,e.g., they may be first in first out (FIFO) queues.

The match engine module 106 may be an example of a transactionprocessing system. The pre-match queue 404 may be an example of apre-transaction queue. The match component 406 may be an example of atransaction component. The post-match queue 408 may be an example of apost-transaction queue. The publish component 410 may be an example of adistribution component. The transaction component may process messagesand generate transaction component results.

In one embodiment, the publish component may be a distribution componentthat can distribute data to one or more market participant computers. Inone embodiment, match engine module 106 operates according to a firstin, first out (FIFO) ordering. The conversion component 402 converts orextracts a message received from a trader via the Market Segment Gatewayor MSG into a message format that can be input into the pre-match queue404.

Messages from the pre-match queue may enter the match component 406sequentially and may be processed sequentially. In one regard, thepre-transaction queue, e.g., the pre-match queue, may be considered tobe a buffer or waiting spot for messages before they can enter and beprocessed by the transaction component, e.g., the match component. Thematch component matches orders, and the time a message spends beingprocessed by the match component can vary, depending on the contents ofthe message and resting orders on the book. Thus, newly receivedmessages wait in the pre-transaction queue until the match component isready to process those messages. Moreover, messages are received andprocessed sequentially or in a first-in, first-out FIFO methodology. Thefirst message that enters the pre-match or pre-transaction queue will bethe first message to exit the pre-match queue and enter the matchcomponent. In one embodiment, there is no out-of-order messageprocessing for messages received by the transaction processing system.The pre-match and post-match queues are, in one embodiment, fixed insize, and any messages received when the queues are full may need towait outside the transaction processing system or be re-sent to thetransaction processing system.

The match component 406 processes an order or message, at which pointthe transaction processing system may consider the order or message ashaving been processed. The match component 406 may generate one messageor more than one message, depending on whether an incoming order wassuccessfully matched by the match component. An order message thatmatches against a resting order in the order book may generate dozens orhundreds of messages. For example, a large incoming order may matchagainst several smaller resting orders at the same price level. Forexample, if many orders match due to a new order message, the matchengine needs to send out multiple messages informing traders whichresting orders have matched. Or, an order message may not match anyresting order and only generate an acknowledgement message. Thus, thematch component 406 in one embodiment will generate at least onemessage, but may generate more messages, depending upon the activitiesoccurring in the match component. For example, the more orders that arematched due to a given message being processed by the match component,the more time may be needed to process that message. Other messagesbehind that given message will have to wait in the pre-match queue.

Messages resulting from matches in the match component 406 enter thepost-match queue 408. The post-match queue may be similar infunctionality and structure to the pre-match queue discussed above,e.g., the post-match queue is a FIFO queue of fixed size. As illustratedin FIG. 4, a difference between the pre- and post-match queues may bethe location and contents of the structures, namely, the pre-match queuestores messages that are waiting to be processed, whereas the post-matchqueue stores match component results due to matching by the matchcomponent. The match component receives messages from the pre-matchqueue and sends match component results to the post-match queue. In oneembodiment, the time that results messages, generated due to thetransaction processing of a given message, spend in the post-match queueis not included in the latency calculation for the given message.

Messages from the post-match queue 408 enter the publish component 410sequentially and are published via the MSG sequentially. Thus, themessages in the post-match queue 408 are an effect or result of themessages that were previously in the pre-match queue 404. In otherwords, messages that are in the pre-match queue 404 at any given timewill have an impact on or affect the contents of the post-match queue408, depending on the events that occur in the match component 406 oncethe messages in the pre-match queue 404 enter the match component 406.

As noted above, the match engine module 106 in one embodiment operatesin a first in first out (FIFO) scheme. In other words, the first messagethat enters the match engine module 106 is the first message that isprocessed by the match engine module 106. Thus, the match engine module106 in one embodiment processes messages in the order the messages arereceived. In FIG. 4, as shown by the data flow arrow, data is processedsequentially by the illustrated structures from left to right, beginningat the conversion component 402, to the pre-match queue, to the matchcomponent 406, to the post-match queue 408, and to the publish component410. The overall transaction processing system operates in a FIFO schemesuch that data flows from element 402 to 404 to 406 to 408 to 410, inthat order. If any one of the queues or components of the transactionprocessing system experiences a delay, that creates a backlog for thestructures preceding the delayed structure. For example, if the match ortransaction component is undergoing a high processing volume, and if thepre-match or pre-transaction queue is full of messages waiting to enterthe match or transaction component, the conversion component may not beable to add any more messages to the pre-match or pre-transaction queue.

Messages wait in the pre-match queue. The time a message waits in thepre-match queue depends upon how many messages are ahead of that message(i.e., earlier messages), and how much time each of the earlier messagesspends being serviced or processed by the match component. Messages alsowait in the post-match queue. The time a message waits in the post-matchqueue depends upon how many messages are ahead of that message (i.e.,earlier messages), and how much time each of the earlier messages spendsbeing serviced or processed by the publish component. These wait timesmay be viewed as a latency that can affect a market participant'strading strategy.

After a message is published (after being processed by the componentsand/or queues of the match engine module), e.g., via a market data feed,the message becomes public information and is publicly viewable andaccessible. Traders consuming such published messages may act upon thosemessages, e.g., submit additional new input messages to the exchangecomputing system responsive to the published messages.

The match component attempts to match aggressing or incoming ordersagainst resting orders. If an aggressing order does not match anyresting orders, then the aggressing order may become a resting order, oran order resting on the books. For example, if a message includes a neworder that is specified to have a one-year time in force, and the neworder does not match any existing resting order, the new order willessentially become a resting order to be matched (or attempted to bematched) with some future aggressing order. The new order will thenremain on the books for one year. On the other hand, an order specifiedas a fill or kill (e.g., if the order cannot be filled or matched withan order currently resting on the books, the order should be canceled)will never become a resting order, because it will either be filled ormatched with a currently resting order, or it will be canceled. Theamount of time needed to process or service a message once that messagehas entered the match component may be referred to as a service time.The service time for a message may depend on the state of the orderbooks when the message enters the match component, as well as thecontents, e.g., orders, that are in the message.

In one embodiment, orders in a message are considered to be “locked in”,or processed, or committed, upon reaching and entering the matchcomponent. If the terms of the aggressing order match a resting orderwhen the aggressing order enters the match component, then theaggressing order will be in one embodiment guaranteed to match.

As noted above, the latency experienced by a message, or the amount oftime a message spends waiting to enter the match component, depends uponhow many messages are ahead of that message (i.e., earlier messages),and how much time each of the earlier messages spends being serviced orprocessed by the match component. The amount of time a match componentspends processing, matching, or attempting to match a message dependsupon the type of message, or the characteristics of the message. Thetime spent inside the processor may be considered to be a service time,e.g., the amount of time a message spends being processed or serviced bythe processor.

The number of matches or fills that may be generated in response to anew order message for a financial instrument will depend on the state ofthe data object representing the electronic marketplace for thefinancial instrument. The state of the match engine can change based onthe contents of incoming messages.

It should be appreciated that the match engine's overall latency is inpart a result of the match engine processing the messages it receives.The match component's service time may be a function of the message type(e.g., new, modify, cancel), message arrival rate (e.g., how many ordersor messages is the match engine module receiving, e.g., messages persecond), message arrival time (e.g., the time a message hits the inboundMSG or market segment gateway), number of fills generated (e.g., howmany fills were generated due to a given message, or how many ordersmatched due to an aggressing or received order), or number of Mass Quoteentries (e.g., how many of the entries request a mass quote).

In one embodiment, the time a message spends:

Being converted in the conversion component 402 may be referred to as aconversion time;

Waiting in the pre-match queue 404 may be referred to as a wait untilmatch time;

Being processed or serviced in the match component 406 may be referredto as a matching time;

Waiting in the post-match queue 408 may be referred to as a wait untilpublish time; and

Being processed or published via the publish component 410 may bereferred to as a publishing time.

It should be appreciated that the latency may be calculated, in oneembodiment, as the sum of the conversion time and wait until match time.Or, the system may calculate latency as the sum of the conversion time,wait until match time, matching time, wait until publish time, andpublishing time. In systems where some or all of those times arenegligible, or consistent, a measured latency may only include the sumof some of those times. Or, a system may be designed to only calculateone of the times that is the most variable, or that dominates (e.g.,percentage wise) the overall latency. For example, some marketparticipants may only care about how long a newly sent message that isadded to the end of the pre-match queue will spend waiting in thepre-match queue. Other market participants may care about how long thatmarket participant will have to wait to receive an acknowledgement fromthe match engine that a message has entered the match component. Yetother market participants may care about how much time will pass fromwhen a message is sent to the match engine's conversion component towhen match component results exit or egress from the publish component.

Mitigating Electronic Data Transaction Request Message Latency Disparity

An exchange computing system may timestamp electronic data transactionrequest messages as they are received and use the timestamp of a messageto determine the time priority assigned to the message. Marketparticipants with faster network connections are able to submit theirelectronic data transaction request messages to the exchange computingsystem faster than other market participants with slower networkconnections. An exchange computing system that processes (e.g., attemptsto match) electronic data transaction request messages in the order theywere received (e.g., based on the timestamp associated with a message)incentivizes market participants to submit messages as quickly aspossible to the exchange computing system. This may involve investingcomputing resources in fast network connections, and may requireconstant upgrading as technology evolves, resulting in a competitionbetween market participants to have the best/fastest network connectionsto the exchange computing system.

Exchange computing systems may attempt to minimize this dependence onspeed, or on the importance of speed, by mitigating the advantagesconferred to the market participants with the fastest connections. Forexample, an exchange computing system may group electronic datatransaction request messages received over an interval together and mayprocess groups of electronic data transaction request messages as ifthey were received at the same time. Or systems may introducerandomization to messages that are grouped together, so that within agroup of messages, time priorities to those messages are randomlyassigned by the exchange computing system. In such systems, a messagereceived earlier than another message in the same interval may not haveany time-based benefit over the later-received message. Groupingmechanisms may involve, for example, grouping messages received over aninterval, and rearranging the order in which the messages are eventuallyprocessed by the hardware matching processor, thus potentiallyminimizing time-based advantages for messages in the same group. Formore information about processing electronic data transaction requestmessages in intervals, see U.S. Patent Publication No. 2017/0046783,filed Jan. 8, 2016, entitled “Mitigation of Latency Disparity in aTransaction Processing System” (“the '783 Publication”), the entirety ofwhich is incorporated by reference herein and relied upon.

As should be understood, as messages are grouped together, each group ofmessages is processed sequentially, so there is a time advantage for amessage to be joined in an earlier group versus being joined to a latergroup.

If an exchange computing system groups messages together based onintervals, and rearranges messages received over the same interval so nomessage in an interval has a timestamp based advantage, then theinterval may be considered to define a range of time, or a level of timeresolution or granularity, beyond which it is no longer advantageous fora market participant to maintain faster network connections and speedsto the exchange computing system. For instance, a market participant maydetermine that the round-trip time between that market participant'sclient computer and the exchange computing system is 2 microseconds. Ifan exchange computing system groups messages received over a10-microsecond interval, the client computer may no longer beincentivized to invest resources to reduce the round-trip time betweenthe client computer and the exchange computing system.

Thus, grouping electronic data transaction request messages togetherover an interval, and rearranging the electronic data transactionrequest messages so they are processed by the match engine module in anorder different from the order that the messages were received by thedata transaction processing system, introduces a latency floor orminimum latency, such that any message that experiences a latency lessthan the minimum latency may not experience any time-based advantageover other messages that are grouped in the same interval. In otherwords, the system does not confer any time-based advantage to anymessage that responds faster than the latency floor. In one embodiment,the latency floor is the interval that is selected by the intervalprocessor 504. A message may be forced to wait until the elapse of theinterval, thus, removing incentives for market participants to submitelectronic data transaction request messages faster than the latencyfloor. A message that experiences an overall latency less than thelatency floor is treated as having arrived at or after the latencyfloor. Thus, market participants may find that investing in technologies(e.g., faster network connections) that enable the market participantsto submit messages that experience a latency less than the latency flooris unnecessary and a waste of computing resources, because there is no,or very little, benefit associated with the faster network connections.

When considering that hundreds or thousands of market participants mayconnect to a data transaction processing system such as an exchangecomputing system, without the interval processor 504, there may alwaysbe a market participant willing to invest a little bit more in terms ofcomputing resources to achieve a time-based advantage over other marketparticipants. The disclosed embodiments may accordingly disincentivizethe need to continually invest computing resources into the fastest andlatest technologies to obtain and maintain as fast a connection aspossible. In some cases, the disclosed embodiments may minimize the needfor market participants to receive information (e.g., a change in theinterest rate, or some other global event that affects futures prices)as fast as possible, because again, the advantages of reacting fasterthan the latency floor are minimized.

In another advantageous application of the disclosed embodiments, a datatransaction processing system such as an exchange computing system mayoffer the ability for market participants to co-locate their servers andmachines in the same facility (e.g., data network center) as the matchengine module, to minimize the latency between the client computer andthe data transaction processing system. If many market participantschoose to co-locate their machines in the same facility as the datatransaction processing system, the market participants may all expectthat their response times are the same. The data transaction processingsystem may thus need to introduce measures to ensure that two marketparticipants in the same facility experience the same delay. Byintroducing a latency floor, the data transaction processing system maynot need to ensure the same response times to commonly co-located marketparticipants. The processing and computational burden of guaranteeingthat two machines experience the same response time (e.g., electronicdata transaction request messages from the machines experience the samelatency in reaching the match engine module) is removed, resulting in animproved and more efficient data transaction processing system.

However, market participants may attempt to overcome such groupingmeasures. For example, market participants may overload the system withmultiple copies of the same electronic data transaction request message,to increase the likelihood that one of the copies of electronic datatransaction request messages is part of an earlier group, or isprocessed first or ahead of other market participants' electronic datatransaction request messages in the same interval or group.

Grouping mechanisms may also incentivize or otherwise influence marketparticipants to submit the last message added to a group or interval tomaximize information advantage over other messages in the same group.Market participants act on available information, and their pricingstrategies (submitted via the electronic data transaction requestmessages, for example) may depend on information, such as theinformation received by the market participants via market data feeds.When an exchange computing system groups together messages based on aninterval, and then applies techniques (e.g., randomization) to mitigatethe receipt time difference between messages in a group, the marketparticipants may be incentivized to wait as long as possible beforejoining that group, because the market participant can then send inmessages that are acting on the most recent market data. In other words,market participants may consider that as long as their messages aregoing to be joined in an interval with a group of other messages, thelater a messages is added to the interval, the more information thatmessage can act upon as compared to other messages in the same intervalbut submitted at an earlier time.

For example, market participant A may submit an electronic datatransaction request message 1 to buy a futures contract Z for a value of70.5. A few microseconds later, a market data feed informs both marketparticipants A and B about a movement in the trade price of a relatedfutures contract Y that changes the value (e.g., subjective value) ofthe futures contract Z. Based on this new information, marketparticipant B may submit electronic data transaction request message 2to buy the same futures contract Z for a value of 70.1. Marketparticipant B accordingly has an information advantage over marketparticipant A. Market participant has a time advantage over marketparticipant B, because the exchange computing system received electronicdata transaction request message 1 before electronic data transactionrequest message 2. However, if the exchange computing system groupselectronic data transaction request messages 1 and 2 in the sameinterval, the exchange computing system essentially removes this timeadvantage of message 1. Thus, if a market participant's message can bethe last message in any given interval, the market participant may haveaccess to more information (e.g., market information) than other marketparticipants whose electronic data transaction request messages arealready in the same interval, without being disadvantaged based on time.

Thus, market participants may try to estimate when an interval closesand attempt to submit their messages at the end of an interval. Anexchange computing system such as the CME may provide historical messagetraffic and processing information to market participants. Thus, marketparticipants can analyze historical message flow and try to estimate howintervals are generated and implemented by an exchange computing system,and then attempt to submit messages later in the interval, so they areacting on more recent information. For example, market participants maybe able to estimate when an interval begins, because the exchangecomputing system may typically begin intervals upon the receipt of amessage. Market participants may also be to estimate average intervallengths based on historical information and may be able to estimatepatterns even when the exchange computing system attempts to use randomintervals.

The disclosed embodiments implement an interval processor that generatesintervals that are random and variable, but also based on the actualmessages that are received by the data transaction processing system andthus highly unpredictable to client computers that cannot know whenother client computers will submit messages, and also realigns marketparticipant incentives so that messages received later in any group maybe processed before messages received earlier in a group.

FIG. 5 illustrates an example computer system 500 including an exampleembodiment of message management module 116. As described in U.S. patentapplication Ser. No. 15/232,224, filed on Aug. 9, 2016, entitled“Systems and Methods for Coordinating Processing of Instructions AcrossMultiple Components” (“the '224 application”), the entirety of which isincorporated by reference herein and relied upon, the exchange computingsystem may be configured to detect the time signal data associated withincoming transactions, or data indicative of a time of receipt of thetransaction. The exchange computing system may augment each electronicdata transaction request message or transaction with time signal data,or data indicative of a time of receipt or time or sequence indicativeof a temporal or sequential relationship between a received transactionand other received transactions, such as a timestamp. The time signaldata may be based on, for example, clock 506, described below.

Message management module 116 includes buffer 502, which may beimplemented as a separate component or as one or more logic components,such as on an FPGA which may include a memory or reconfigurablecomponent to store logic and processing component to execute the storedlogic, e.g. computer program logic, stored in a memory 204, or othernon-transitory computer readable medium, and executable by a processor202, such as the processor 202 and memory 204 described with respect toFIG. 2, to cause the processor 202 to, or otherwise be operative toreceive and store, e.g., temporarily, electronic data transactionrequest messages from client computers, such as 510 and 512 over networkconnections 516 and 518 respectively. Buffer 502 may be of fixed size,or of variable size.

Buffer 502 may be implemented with pointers, as described above, so thata transaction processor or an application can rapidly access any of theelectronic data transaction request messages held in the buffer 502 inany desirable sequence. For instance, as discussed below with respect toFIG. 6, the buffer 502 may include positions that may be identifiablewith memory address pointers.

Message management module 116 includes interval processor 504, which maybe implemented as a separate component or as one or more logiccomponents, such as on an FPGA which may include a memory orreconfigurable component to store logic and processing component toexecute the stored logic, e.g. computer program logic, stored in amemory 204, or other non-transitory computer readable medium, andexecutable by a processor 202, such as the processor 202 and memory 204described with respect to FIG. 2, to cause the processor 202 to, orotherwise be operative to, determine, e.g., automatically, occurrencesof events and control grouping of electronic data transaction requestmessages and/or transferring of data out of buffer 502, and/or the sizeof buffer 502.

Message management module 116 includes clock 506, which may be ahardware unit, such as the Solarflare Precision Time Protocol (PTP)™hardware. Clock 506 may provide a source of time, which is used toaugment electronic data transaction request messages with time signaldata and, as described herein, may be used by interval generator 504 todetermine grouping of electronic data transaction request messages.

In one embodiment, the interval processor 504 may determine anoccurrence of a first event and a subsequent occurrence of a secondevent. In one embodiment, the first event defines the beginning of aninterval or time. In particular, in one embodiment, the time intervalmay begin to elapse upon receipt, e.g. the first event, of an incomingorder subsequent to a prior elapse of a time interval. The intervalprocessor 504 may be configured to detect when buffer 502 receives anelectronic data transaction request message that begins a new, e.g.,current, interval.

The interval processor 504 may generate a minimum interval time orduration. The interval processor 504 may also generate an intervalextension number, which may be a maximum extension number. The intervalprocessor 504 may also generate a per extension time. One, some or allof the minimum interval time, interval extension number, and perextension time may be randomly or pseudo randomly generated for eachdifferent interval calculated by the interval processor 504. Theinterval processor 504 dynamically determines an interval to be appliedto one or more electronic data transaction request messages received bythe buffer as the minimum interval time plus the interval extensionnumber times the per extension time.

After an interval begins (e.g., upon receipt of an electronic datatransaction request message by the buffer 502), the interval processor504 automatically assigns the minimum interval time as the intervalduration for the interval. For each subsequent electronic datatransaction request message received by the buffer 502 before theminimum interval time expires and up to the maximum extension number ofelectronic data transaction request messages, the interval processor 504increases or extends the interval duration for the interval by the perextension time. When the interval elapses (i.e., the interval durationelapses), the interval processor 504 closes the interval. For the nextinterval, the interval processor 504 generates new values for theminimum interval time, interval extension number and per extension time,and then extends the duration of the interval based on the number ofmessages actually received by the data transaction processing systembefore the interval elapses.

In one embodiment, the interval processor 504 may generate a minimuminterval time, an interval extension number, and a maximum intervaltime. In this embodiment, the interval is closed after the first of: anumber of messages equaling the interval extension number is received,or the maximum interval time is reached. Thus, the interval is closedupon reaching a certain number of messages, or if the maximum intervaltime elapses.

In one embodiment, the interval processor 504 may detect an event thatinitiates or begins another interval after one interval closes. Asexplained herein, the duration of an interval is extendible, and isbased on the actual messages that are received by the data transactionprocessing system. For example, the interval duration may be extended anumber of different times, depending on the interval extension numbergenerated by the interval processor 504, and depending on how manyelectronic data transaction request messages are actually received bythe data transaction processing system before the interval elapses.Thus, the interval processor 504 is configured to generate new intervaldurations for each group of electronic data transaction request messagesthat are stored in the buffer 502. In one embodiment, the buffer 502holds electronic data transaction request messages that belong to or arepart of the same interval. In one embodiment, all messages that are heldby buffer 502 at the same time are part of the same interval and will beforwarded to the match engine module in a group, as described below.

In one embodiment, the interval processor 504 determines whether anelectronic data transaction request message is received during aninterval calculation, or if the electronic data transaction requestmessage triggers the beginning of a new interval.

For example, the interval processor 504 may randomly generate a minimuminterval time as 10 microseconds, an interval extension number as 5electronic data transaction request messages, and a per extension timeof 2 microseconds, and store these values in a memory associated withinterval processor 504.

At time t=0, the message management module 116 receives electronic datatransaction request message 1, which may be stored in buffer 502. Theinterval processor 504 determines that electronic data transactionrequest message is a first event that triggers a new interval. Theinterval processor 504 assigns the minimum interval time, 10microseconds, as the total interval time.

At time t=3 microseconds, the message management module 116 receiveselectronic data transaction request message 2, which may be stored inbuffer 502. Because the total interval time has not yet elapsed,electronic data transaction request message 2 extends the total intervaltime as described herein. In particular, the interval processor 504 addsthe per extension time, i.e., 2 microseconds, to the total interval timeof 10 microseconds and updates the total interval time to be 12microseconds.

For each electronic data transaction request message received before theinterval elapses, the total interval time is increased by the perextension time until the total interval time has been increased by theinterval extension number. An interval elapses when the intervalprocessor 504 determines that the total interval time has passed sincethe interval began. The total interval time can be extended as long as anew electronic data transaction request message (up to the intervalextension number) is received before the interval elapses.

For example, as discussed above, the total interval time is modified to12 microseconds after receipt of electronic data transaction requestmessage 2 at time t=3 microseconds. If message management modulereceives electronic data transaction request message 3 at time t=11microseconds, the interval processor 504 adds the per extension time,i.e., 2 microseconds, to the total interval time of 12 microseconds andupdates the total interval time to be 14 microseconds.

If message management module receives electronic data transactionrequest message 4 at time t=12 microseconds, the interval processor 504adds the per extension time, i.e., 2 microseconds, to the total intervaltime of 14 microseconds and updates the total interval time to be 16microseconds.

If the message management module does not receive any more electronicdata transaction request message before 16 microseconds elapses, i.e.,the current interval closes, the interval processor 504 groupselectronic data transaction request messages 1, 2, 3 and 4 together. Thegroup may then be re-sequenced by sequencer 508 as described herein.

It should accordingly be appreciated that the interval processor 504dynamically determines an interval based on the values for the minimuminterval time, interval extension number, and the per extension time,which may be random, and also based on the actual message flow ofelectronic data transaction request messages received by the exchangecomputing system. For example, the interval duration is based on themessages actually received by the exchange computing system before thatinterval elapses. A message that is received by the buffer 502 justbefore the interval elapses then may (as long as the interval extensionnumber has not yet been reached) extend the interval by the perextension time.

The interval for any one group of messages grouped together becomesdifficult, if not impossible, for a market participant to estimate orpredict. Yet, because the interval creation is based on the disclosedruleset, the interval can be recreated by customers, e.g., forpost-transaction testing/review and increasing overall transparency. Theinterval processor 504 creates intervals that are random (because thevalues assigned for the minimum interval time, interval extensionnumber, and the per extension time for each interval are randomlygenerated by the interval processor 504), variable (because they differfor different groups/intervals) and are based on, or extended based on,the messages actually received by the data transaction processing systembefore the interval elapses.

After an interval is closed, message management module 116 may beginstoring newly received messages into another buffer (not shown) or maytransfer the messages to a sequencer 508. Interval processor 504 maydetect events related to the newly received messages as discussed hereinand may also determine new random values of next interval's minimuminterval time, interval extension number, and the per extension time.

Message management module 116 includes sequencer 508, which may beimplemented as a separate component or as one or more logic components,such as on an FPGA which may include a memory or reconfigurablecomponent to store logic and processing component to execute the storedlogic, e.g. computer program logic, stored in a memory 204, or othernon-transitory computer readable medium, and executable by a processor202, such as the processor 202 and memory 204 described with respect toFIG. 2, to cause the processor 202 to, or otherwise be operative torearrange electronic data transaction request messages in buffer 502and/or forward electronic data transaction request messages in buffer502 to match engine module 106. In one embodiment, the messagemanagement module includes a transmitter that transmits or forwardsmessages from the buffer to the transaction processor.

As discussed above, electronic data transaction request messages areadded to the buffer 502 as they are received by the data transactionprocessing system. Thus, the messages are initially held by buffer 502in the order they are received by the data transaction processingsystem, i.e., in order of the receipt timestamp imparted onto eachmessage. Upon the close of an interval, buffer 502 contains all theelectronic data transaction request messages associated with theinterval in the order they were received by the data transactionprocessing system. Sequencer 508 is operative to rearrange the messagesin the buffer 502 so that they are processed by the match engine modulein an order different from the order they were received by the datatransaction processing system.

In one embodiment, sequencer 508 may rearrange the pointers associatedwith the positions in the buffer 502. In one embodiment, sequencer 508may control the transfer of messages from the buffer 502 to the matchengine module. Or, sequencer 508 may remove messages from the buffer 502and place them in queues, and re-insert the messages, in a differentorder, back into the buffer 502. Thus, sequencer 508 may be implementedin a variety of ways to cause the contents of buffer 502 to berearranged before being processed, e.g., matched, by the match enginemodule.

In one embodiment, interval processor 504 causes the contents of buffer502 to be transferred to sequencer 508. Alternatively, sequencer 508extracts groups of electronic data transaction request messages frombuffer 502. Sequencer 508 identifies an order in which electronic datatransaction request messages should be forwarded to the match enginemodule 106. Sequencer 508 may be configured to store electronic datatransaction request messages received or extracted from buffer 502 intoa plurality of different queues. The sequencer 508 may perform thesefunctions by setting pointers for the messages in buffer 502, asdescribed herein. Or, the sequencer 508 may physically move the messagesto other queues, as described herein. Thus, the sequencer 508 mayrearrange/reorganize/reorder the data physically and/or logically, etc.

Sequencer 508 may rearrange messages in buffer 502 so that they areforwarded to match engine module in an order or sequence different thana sequence based on the time of receipt of a message by the datatransaction processing system.

For example, sequencer 508 may traverse all the messages received frombuffer 502 in reverse chronological order, i.e., reverse of the order inwhich the electronic data transaction request messages were received bythe data transaction processing system.

In one embodiment, sequencer 508 places (e.g., physically, or logically)electronic data transaction request messages into different queues basedon characteristics of the electronic data transaction request messages.In particular, sequencer 508 places electronic data transaction requestmessages of the same type in the same queue. Sequencer 508 storesnew/modify limit orders into a secondary queue, e.g., a Limit OrderQueue. Sequencer 508 stores fill and kill orders into a secondary queue,e.g., a FAK Order Queue. It should be appreciated that limit ordersdiffer from FAKs in that limit orders are allowed to rest on the booksif their associated quantity is not all satisfied, whereas FAK ordersare not allowed to rest, i.e., they are not added to the resting orderbooks. In one embodiment, the data transaction processing system mayprioritize limit orders over FAKs because FAK orders may not contributeto the liquidity of the electronic marketplace.

Sequencer 508 leaves cancels where they are in the buffer 502. Thus,after sequencer 508 traverses the buffer 502 in an order, e.g., reversechronological order, buffer 502 may be empty, or may only contain cancelmessages. Alternatively, sequencer 508 may also transfer cancel messagesinto a secondary queue, e.g., a Cancel Order Queue.

Sequencer 508 then re-populates buffer 520 with messages from thesecondary queues in a different order than the order the messages wereinitially stored in the buffer 502. In particular, sequencer 508 thentraverses each secondary queue in order. For example, sequencer 508traverses the Limit Order Queue in FIFO order and transfers messages,one by one, into the first available spot in buffer 502. Sequencer 508then traverses the Cancel Order Queue (if they were transferred out ofthe buffer 502 into a secondary queue) in FIFO order and transfersmessages, one by one, into the first available spot in buffer 502.Sequencer 508 also traverses the FAK Order Queue in FIFO order andtransfers messages, one by one, into the first available spot in buffer502. Buffer 502 now contains the new/modify limit orders initiallyreceived by the buffer 502 during an interval first, followed by cancelorders, and then FAK orders at the end.

The interval processor 504 then causes the orders from the buffer 502 tobe transmitted to the match engine module 106 which then processes thetransactions, based on the sequencing imparted by sequencer 508/buffer502 mechanism. The sequencing described herein processes electronic datatransaction request message within the same interval in reverse of theorder in which the electronic data transaction request messages werereceived by the data transaction processing system (e.g., LIFO), andcategorized by type (limit orders first (orders which have the potentialto rest, if they are not fully satisfied in the first match attempt),then cancels, then fill and kills or fill or kills (i.e., orders whichwill not rest even if they are not fully satisfied in the first matchattempt)), incentivizing market participants to not submit electronicdata transaction request messages that are first in an interval, thusdeterring from the need to submit electronic data transaction requestmessages first/immediately.

In other words, market participants' incentives are realigned becausedifferent positions within an interval are associated with both risksand rewards, such that market participants do not perceive any oneposition in an interval as being better than another, and further suchthat market participants do not attempt to submit messages within acertain portion of an interval.

For example, by utilizing the interval processor 504 and sequencer 508to achieve the varying time intervals for each time interval, which isbased on messages actually received before the elapse of an interval:

messages that are early in a group are processed last in that group(risk), but might miss the group entirely and join an earlier group(reward);

messages received in the middle of a group are less likely to beprocessed first (risk), but have a high certainty of being in a currentgroup versus a later group (reward); and

messages received near the end of a group could miss the groupcompletely and be added to the next group (risk) but have a highprobability of being processed first (reward).

The data transaction processing system receives a continuous flow ofmessages and grouping messages in varying intervals as described hereinrealigns incentives so that market participants do not perceive muchvalue in controlling how their messages are grouped. The disclosedsystem is a technological solution to market participants' clientcomputers attempting to optimize the position of their messages withinan interval. In the disclosed system, each grouping, and each positionwithin a group, is associated with advantages and disadvantages, andbecause the close of each interval is random and based on the actualmessage flow, market participants may no longer need to continue toinvest in the fastest connections to the data transaction processingsystem, or to attempt to estimate when an interval will close, and thedata transaction processing system can also reduce the computingresources required to receive and manage a high and increasingtransmission rate of electronic data transaction request messages.

The interval processor 504 dynamically determines the end of an intervalbased on random values and actual message flow, making the interval bothunpredictable in real time but deterministic and thus equitable (e.g.,can be recreated at the end of the trading day by customers forpost-trade analysis). The disclosed embodiments deter marketparticipants from attempting to submit electronic data transactionrequest messages near the end of a group of electronic data transactionrequest messages that are received within the same interval.

After electronic data transaction request messages are rearranged bysequencer 508, the electronic data transaction request messages areforwarded to the match engine module. In one embodiment, the messagemanagement module includes a transmitter that transmits or forwardsmessages from the buffer to the match engine. The match engine module106 determines a result, referred to as a match event, indicative, forexample, of whether the order to trade was matched with a prior order,or reflective of some other change in a state of an electronicmarketplace, etc. As used herein, match events generally refer toinformation, messages, alerts, signals or other indicators, which may beelectronically or otherwise transmitted or communicated, indicative of astatus of, or updates/changes to, a market/order book, i.e. one or moredatabases/data structures which store and/or maintain data indicative ofa market for, e.g. current offers to buy and sell, a financial product,described in more detail below, or the match engines associatedtherewith.

Sequencer 508 may extract and re-populate (logically or physically)electronic data transaction request messages from and into buffer 502based on a variety of different sorting rules. For example, thesequencer 508 and buffer 502 may be configured to sort electronic datatransaction request messages received in a same interval as determinedby the interval processor 504 by quantity, so that messages in the sameinterval associated with a smaller quantity are sent first to the matchengine module. Or, the sequencer 508 and buffer 502 may be configured tosort electronic data transaction request messages received in a sameinterval as determined by the interval processor 504 by the number ofmost unique quantities, so that messages in the same interval associatedwith a unique quantity are prioritized over messages associated with acommonly occurring quantity. Or, the message management module may sortelectronic data transaction request messages received in an intervalrandomly, e.g., based on a random starting point.

As discussed herein, in one embodiment, the messages from buffer 502 aretransferred out of buffer 502 upon close of an interval to sequencer508. Alternatively, the sequencer 508 may be operative to rearrangepointers associated with buffer 502 to impart a sequence, so themessages may continue to be held in the buffer 502. If the messages arekept in buffer 502 after the close of an interval, the messagemanagement module 116 may include additional buffers (not shown) forreceiving and storing electronic data transaction request messagesassociated with subsequent intervals.

It should be appreciated that in the disclosed example, the match enginemodule processes new limit orders before fill and kill (FAK) messages,regardless of the initial sequence in which the electronic datatransaction request messages were received by the data transactionprocessing system. In one embodiment, the interval processor 504 may beconfigured to forward all new limit orders and cancel orders to thematch engine module before fill and kill (FAK) messages. As discussedherein, this sequencing, in conjunction with the dynamically extendibleinterval, prevents market participant estimation of message positionwithin an interval such that continuous investment in computingresources for the fastest network connections is not valuable for marketparticipants. It should be appreciated that the disclosed embodiments donot require market participants to modify their existing messagingpatterns or protocols.

FIG. 6 illustrates an example buffer 502 holding electronic datatransaction request messages M1 through M6. Buffer 502 includespositions 1 through 6, where the first message received is stored inposition 1, the second message received is stored in position 2, etc.Interval processor 504 determines that electronic data transactionrequest messages M1 through M6 should be grouped together as describedherein. Each of the positions may be associated with a pointer, whichmay be used to control the order in which messages in the same group areactually forwarded to and processed by the match engine module.

As shown in FIG. 7, the sequencer 508 includes a plurality of secondaryqueues 508A and 508B. In one embodiment, the interval processor 504 maytransfer messages from the buffer 502 to the sequencer 508.Alternatively, the sequencer 508 may pull or extract messages from thebuffer 502.

Interval processor 504 transfers messages from buffer 502 to sequencer508 including secondary queues 508A and 508B. In particular, intervalprocessor 504 transfers limit messages to queue 508A, and fill and killmessages to queue 508B. Moreover, the messages are transferred to queuesin reverse chronological order from the order of receipt, so that M5,the last received FAK order (because it was placed initially in position5 in buffer 502) is placed in position 1 of queue 508B.

Interval processor 504 repopulates buffer 502 with the messages fromqueues 508A and 508B. Buffer 502 is repopulated first with orders fromqueue 508A, and then with orders from queue 508B. Moreover, the firstpositions of the queues are emptied first, so that M5 in position 1 ofqueue 508B is the first message removed from queue 508B to repopulatebuffer 502.

FIG. 9 illustrates an example computer implemented method 900 formitigating disparities in latencies of electronic data transactionrequest messages by a data transaction processing system in which dataobjects are transacted by a hardware matching processor that matcheselectronic data transaction request messages for the same one of thedata objects based on multiple transaction parameters received fromdifferent client computers over a data communication network.Embodiments may involve all, more or fewer actions indicated by theactions of FIG. 9. The actions may be performed in the order or sequenceshown or in a different sequence.

At step 902, method 900 includes, upon an occurrence of an event,determining the beginning of an interval having an extendible intervalduration. The interval may be triggered due to a receipt of any one ofthe plurality of electronic data transaction request messages, forexample.

At step 904, method 900 includes, for each electronic data transactionrequest message up to a maximum extension number received by the datatransaction processing system after the occurrence of the event andbefore an elapse of the interval, extending the interval duration by aper extension time. Thus, an interval may be extended based on messagesactually received before the interval elapses.

At step 906, method 900 includes, storing electronic data transactionrequest messages received by the data transaction processing systemafter the occurrence of the event and before the elapse of the intervalin a buffer in a first sequence based on the order in which theelectronic data transaction request messages were received by the datatransaction processing system.

At step 908, method 900 includes, upon the elapse of the interval,forwarding the electronic data transaction request messages in thebuffer to a hardware matching processor in a second sequence differentfrom the first sequence, such that at least one electronic datatransaction request message received by the data transaction processingsystem after another electronic data transaction request message isprocessed by the hardware matching processor before the anotherelectronic data transaction request message.

In an embodiment, the method 900 includes determining a new, potentiallydifferent interval duration for each group of electronic datatransaction request messages that are grouped together, and re-arranged,before being forwarded to a transaction processor for matching. Thetransaction processor may be implemented in a match engine module, suchas the match engine module 106 described in connection with FIG. 4.Because the transaction processor/match engine module may be configuredto process messages in FIFO manner, the sequencer 508's sequencingdetermines the sequence in which the match engine module will transactthe electronic data transaction request messages. The sequencer 508sends messages to the match engine module such that at least oneelectronic data transaction request message received by the datatransaction processing system after another electronic data transactionrequest message is processed by the transaction processor before anotherelectronic data transaction request message. For example, an electronicdata transaction request message of a first type (e.g., a limit order)received by the data transaction processing system before anotherelectronic data transaction request message of the same type (e.g.,another limit order) may be process later than the later-receivedelectronic data transaction request message.

Although all the intervals may follow the same ruleset as describedherein, the values used for the initial interval duration, the number ofextensions allowed, and the per extension time added for each extensionmay be re-calculated by the interval processor 504 for each newinterval.

Data and/or Message Compression

As discussed above, the transaction processor, in one embodiment, is ahardware matching processor that is configured to attempt to match orallocate, as described herein, incoming messages (e.g., from the buffer)with one or more previously received, but not yet matched, messages,i.e., limit orders to buy or sell a given quantity at a given price,referred to as “resting” messages or orders, stored in an order bookdatabase, wherein each resting order is contra to the incoming order andhas a favorable price relative to the incoming order. Matching canrequire a high amount of computing resources, and the computingresources expended to match an electronic data transaction requestmessage can vary based on the current state of the order book when theelectronic data transaction request message is processed by the matchingcomponent, e.g., enters the match component 406. Moreover, marketparticipants may modify their trading strategies within a fewmicroseconds and send additional electronic data transaction requestmessages modifying previously sent electronic data transaction requestmessages within a few microseconds. As discussed herein, groupingmessages received over an interval and re-sequencing grouped messagesbefore they are processed (e.g., for matching) may mitigate the effectsof latency disparity between competing messages. The disclosedembodiments also advantageously facilitate improved processing ofgrouped messages by compressing or pre-processing messages before theyare forwarded to the match engine module.

U.S. Patent Publication No. 2015/0262298, assigned to the assignee ofthe present application, describes storing messages in a buffer, andallowing a subsequently received incoming transaction/order to modify orcancel a stored received incoming order prior to a forwarding thereof tothe match engine.

U.S. Patent Publication No. 2016/0086268 (“the '268 Publication”),assigned to the assignee of the present application, describescollecting orders during an order accumulation period, where one of theorders specifies modifying or canceling a previously submitted orderthat has also been collected in the same order accumulation period. Theorder that specifies modifying or canceling the previously submitted isprocessed in the buffer.

FIG. 10 illustrates an example computer system 1000 including an exampleembodiment of message management module 116. Message management module116 in system 1000 includes many of the same components as messagemanagement module 116 in system 500, and components that are numberedthe same in systems 500 and 1000 are similar and perform similarfunctions. Like the message management module 116 in system 500, themessage management module 116 in system 1000 includes buffer 502,interval processor 504, clock 506 and sequencer 508.

Message management module 116 also includes a compressor 1002, which maybe implemented as a separate component or as one or more logiccomponents, such as on an FPGA which may include a memory orreconfigurable component to store logic and processing component toexecute the stored logic, e.g. computer program logic, stored in amemory 204, or other non-transitory computer readable medium, andexecutable by a processor 202, such as the processor 202 and memory 204described with respect to FIG. 2, to cause the processor 202 to, orotherwise be operative to compress, combine, reduce, and/or deleteelectronic data transaction request messages in the buffer 502 and/orsequencer 508. For example, if messages are transferred from buffer 502to sequencer 508 as discussed above, the compressor 1002 may beconfigured to communicate with and compress messages in sequencer 508.The compressor 1002 may be a compressing processor.

Compressor 1002 is configured to, in one embodiment, compare electronicdata transaction request messages in the buffer 502. In particular,compressor 1002 compares characteristics of electronic data transactionrequest messages in the buffer 502.

In one embodiment, the compressor 1002 determines the source for each ofthe electronic data transaction request messages. The compressor 1002may determine that two messages originate from the same source if themessages are determined to originate from the same IP (internetprotocol) addresses. Alternatively, compressor 1002 may determine thattwo messages originate from the same source if the messages areassociated with the same customer account. In one embodiment, the systemmay be configured to conclude that orders or messages that originatefrom the same trading firm are from the same source. Additional examplesand details of how a system may determine whether messages aretransmitted by or originate from the same source or entity are describedin U.S. Patent Publication No. 2007/0118460 entitled “Detection ofintra-firm matching and response thereto” and filed on Nov. 17, 2006,and U.S. Patent Publication No. 2015/0026033 entitled “EfficientSelf-Match Prevention in an Electronic Match Engine” and filed Oct. 3,2014, both of which are incorporated by reference herein in theirentireties and relied upon.

The compressor 1002, in one embodiment, eliminates or consolidateselectronic data transaction request messages in the buffer 502 thatoriginate from the same source. For example, some client computers maysend multiple electronic data transaction request messages that areredundant to each other. Some trading firms have hundreds of clientcomputers that are programmed to perform an action, e.g., submit anelectronic data transaction request message, in response to detecting anevent. Each of the client computers may send an electronic datatransaction request message to the exchange computing system, and theexchange computing system (and match engine) must then receive andprocess each of the duplicative electronic data transaction requestmessages. The compressor 1002 recognizes such duplicative messages andeither consolidates them, or removes them, depending on the message.

For example, the compressor 1002 may detect multiple electronic datatransaction request messages from the same source, where the requestedtransaction is to cancel a previously submitted electronic datatransaction request message. The previously submitted electronic datatransaction request message may have been send just a few microseconds,or a few minutes, or a few hours before the corresponding cancelmessages are sent. Thus, the previously submitted electronic datatransaction request message may be in the buffer 502 or may have alreadybeen forwarded to the match engine module or may have already beenprocessed by the match engine module. In one embodiment, the compressor1002 detects whether multiple electronic data transaction requestmessages in the buffer are from the same source and request cancellationof a previously sent message. The compressor 1002 may remove all but oneof the cancel messages from the buffer 502. Removal of a message fromthe buffer 502 may comprise deleting the message from the memory.

As another example, the compressor 1002 may detect multiple electronicdata transaction request messages from the same source, where therequested transaction is to modify a previously submitted electronicdata transaction request message. The previously submitted electronicdata transaction request message may have been send just a fewmicroseconds, or a few minutes, or a few hours before the correspondingmodify messages are sent. Thus, the previously submitted electronic datatransaction request message may be in the buffer 502, or may havealready been forwarded to the match engine module, or may have alreadybeen processed by the match engine module. In one embodiment, thecompressor 1002 detects whether multiple electronic data transactionrequest messages in the buffer are from the same source and requestmodification of a previously sent message. The compressor 1002 maycompress the multiple electronic data transaction request messages intoone new electronic data transaction request message that represents thenet effects of the modifications represented by the multiple electronicdata transaction request messages and delete the multiple electronicdata transaction request messages. Or, compressor 1002 may modify one ofthe multiple electronic data transaction request messages so that itrepresents the net effects of the modifications represented by themultiple electronic data transaction request messages, and then deleteall of the other multiple electronic data transaction request messages.

For example, the compressor 1002 may detect multiple electronic datatransaction request messages from the same source, where each messageincludes a transaction request (new order) to purchase or sell aquantity of the same financial instrument. The compressor 1002 maycompress the multiple electronic data transaction request messages intoone new electronic data transaction request message that represents thenet effects of the multiple electronic data transaction request messagesand delete the multiple electronic data transaction request messages.Or, compressor 1002 may modify one of the multiple electronic datatransaction request messages so that it represents the net effects ofthe multiple electronic data transaction request messages, and thendelete all of the other multiple electronic data transaction requestmessages. The compressor 1002 may, in one embodiment, net multiplemessages such that the multiple messages are replaced by a singlemessage in the buffer, where the single message, when processed by thematch engine, has the same impact on the electronic order book as wouldbe had if the multiple messages had been processed by the match engine.

In one embodiment, compressor 1002 compares messages of the same type toeach other. For example, compressor 1002 may compress all FAK orders atthe same price received from the same source, ignoring quantity, intoone message.

In one embodiment, the compressor 1002 detects whether a cancel ormodify message refers to, or cancels or modifies, respectively, amessage that is currently in the buffer 502, i.e., a target electronicdata transaction request message, and if so, performs the requisiteaction, e.g., cancels or modifies, the target electronic datatransaction request message.

It should be appreciated that removing/deleting messages from the buffer502 reduces the number of messages that need to be processed by thematch engine module, thus reducing the processing load on the hardwarematching processor. By performing such preprocessing or compression, thecompressor 1002 reduces the number of messages transmitted to the matchengine module, thus reducing overall processing latency. Each messageprocessed by the transaction processor, regardless of the results of themessage processing, requires computing time and resources. Computingresources that can be allocated may include memory, CPU processingcycles, cores or threads dedicated to performing specific tasks. Eachmessage processed by the transaction processor, regardless of theresults of the message processing, uses up some of the transactionprocessor's computing resources and adds to the latency of the datatransaction processing system. For example, the match component 406,which may be a hardware data transaction processor, may read thecontents of each incoming message. A processing thread may be dedicatedfor reading message contents. If the number of messages read/processedby the match component 406 are reduced, the overall computing resourcesexpended to process messages by the transaction processor is alsoreduced. Thus, by compressing the number of messages, including deletingmessages as described herein, that are forwarded to the match enginemodule, the compressor 1002 reduces the processing load on the matchengine module.

It should be appreciated that in one embodiment, compressor 1002 reducesthe electronic data transaction request messages from the buffer 502based solely on the contents of the electronic data transaction requestmessages in the buffer. The interval used by the interval processor 504thus has an effect on which electronic data transaction request messagesare compressed by compressor 1002. In other words, the compression maybe based on achieving computational efficiencies by reducing redundantmessages in the buffer 502. Which messages will be in the buffer at thesame time, e.g., collected by buffer 502 in the same time interval, maynot be known by any of the market participants at the time of messagesubmission, because, as described above, the buffer interval may berandomized and/or may be based on the actual messages received by thedata transaction processing system.

In one embodiment, the compressor 1002 does not need messages to referto each other in order to compress messages. As discussed above, the'268 Publication requires that a message refer to an already submittedmessage. Compressor 1002 compresses messages after a common interval,during which a group of messages, is defined. Once messages are decidedto be in the same group, the compressor 1002 eliminates/compresses/netsmessages based on the contents of the buffer/group, without any need forthe messages to refer to any other message. Thus, compressor 1002reduces the need for traders to keep track of which messages werepreviously submitted to the data transaction processing system, andwhether the previously submitted messages have already been processed bythe transaction processor, or whether the previously submitted messagesare still in the buffer. Thus, compressor 1002 increases the flexibilityand convenience with which market participants can submit messages.

In one embodiment, even if messages specifically refer to anothermessage, the compressor 1002 can compress multiple redundant messagesthat all refer to a same message. FIG. 11A illustrates example buffer1102 holding electronic data transaction request messages M1 through M6.Buffer 1102 may be similar to buffer 502 described herein. Buffer 1102includes positions 1 through 6, where the first message received isstored in position 1, the second message received is stored in position2, etc. In one embodiment, interval processor 504 determines thatelectronic data transaction request messages M1 through M6 should begrouped together as described herein. Each of the positions may beassociated with a pointer, which may be used to control the order inwhich messages in the same group are actually forwarded to and processedby the match engine module.

As shown in FIG. 11A, the electronic data transaction request messagesmay be associated with different sources, e.g., market participants ortraders, T1, T2 and T3. As shown in FIG. 11A, the buffer 1102 is in astate where four of the six messages are from the same source, sourceT1. In particular, message management module determines that messagesM1, M3, M4, and M6 are all submitted by source T1, e.g., Trader 1. Forexample, message management module may determine that each of messagesM1, M3, M4, and M6 originate from the same IP address. Compressor 1002may additionally determine that messages M3, M5, and M6 are redundant orduplicative of each other, because each of these messages contain aninstruction to cancel the same message M1 and are from the same source.Compressor 1002 then eliminates all but one of messages M3, M5 and M6.As shown in FIG. 11B, compressor 1002 eliminates messages M5 and M6,reducing the number of messages in buffer 1102 from six to four.

In one embodiment, the compressor 1002 may eliminate the message basedon message elimination rules, such as eliminate the first redundantmessage received (e.g., M3), or eliminate the last redundant messagereceived (e.g., M6), or eliminate the redundant message received betweenthe first and last redundant messages (e.g., M5).

When a message refers to another message, the referred to message may bethe reference or target message. In the example of FIG. 11A, M1 is thereference or target message of messages M3, M5 and M6, because messagesM3, M5 and M6 refer to message M1.

Additionally, or alternatively, the compressor 1002 may determinewhether a message and a reference or target message are both in thebuffer 1102, and if so, compressor 1002 may perform the action requestedby the message. Referring back to FIG. 11B, after compressor 1002removes two of the three redundant messages (M3, M5 and M6), leavingonly M3, the compressor 1002 may process M3 and cancel M1, before eitherM1 or M3 is forwarded to the transaction processor. The result ofprocessing message M3 is shown in FIG. 11C, illustrating buffer 1102only containing two messages. Compressor 1002 accordingly has compressedthe electronic data transaction request messages in buffer 1102 from sixmessages to two messages.

It should be appreciated that compressor 1002 would compress messagesM3, M5 and M6 regardless of whether the reference message M1 is also inbuffer 1102. In one embodiment, the compressor 1002 may be configured toperform all redundant processing (e.g., compressing messages M3, M5 andM6 because they are redundant) before any reference message processing(e.g., determining that M3 and its reference message M1 are both in thebuffer 1102 at the same time, and accordingly processing M3).

Compressor 1002 may similarly compress modify messages that are from thesame source and refer to the same reference or target message. FIG. 12Aillustrates example buffer 1202 holding electronic data transactionrequest messages M1 through M6. Buffer 1202 may be similar to buffer 502described herein. Buffer 1202 includes positions 1 through 6, where thefirst message received is stored in position 1, the second messagereceived is stored in position 2, etc. In one embodiment, intervalprocessor 504 determines that electronic data transaction requestmessages M1 through M6 should be grouped together as described herein.Each of the positions may be associated with a pointer, which may beused to control the order in which messages in the same group areactually forwarded to and processed by the match engine module.

As shown in FIG. 12A, message M1 is related to financial instrument FC1.Messages M3, M5 and M6 each modifies the quantity associated withmessage M1. Thus, messages M1, M3, M5 and M6 all related to the samefinancial instrument, FC1. Compressor 1002 determines that messages M3and M5 both modify the quantity to be acquired in target message M1. Inone embodiment, compressor 1002 applies the changes specified in themost recently received message from M3 and M5 (i.e., M5) and deletes theother message(s) (i.e., M3). FIG. 12B illustrates buffer 1202 aftercompressor 1002 has compressed messages M3 and M5.

Additionally, or alternatively, the compressor 1002 may determinewhether a message and a reference or target message are both in thebuffer 1202, and if so, compressor 1002 may perform the action requestedby the message. Referring back to FIG. 12B, after compressor 1002removes one of the two duplicative messages (M3 and M5), leaving onlyM5, the compressor 1002 may process M5 and modify M1, before either M1or M5 is forwarded to the transaction processor. The result ofprocessing message M5 is shown in FIG. 12C, illustrating buffer 1202only containing four messages. Compressor 1002 accordingly hascompressed the electronic data transaction request messages in buffer1202 from six messages to four messages.

It should be appreciated that compressor 1002 would compress messages M3and M5 regardless of whether the reference message M1 is also in buffer1202. In one embodiment, the compressor 1002 may be configured toperform all duplicative processing (e.g., compressing messages M3 and M5because they are similar and both modify the quantity in the samereference message) before any reference message processing (e.g.,determining that M5 and its reference message M1 are both in the buffer1202 at the same time, and accordingly processing M5).

In one embodiment, if messages M3 and M5 contain an instruction to addor remove quantity (instead of specifying the new quantity), compressor1002 nets the effects of each message that adds or removes quantity. Forexample, if M3 includes an instruction to increase the quantity of M1 by2 units, and M5 includes an instruction to increase the quantity of M1by 6 units, compressor 1002 nets the effects of messages and M3 and M5,and modifies one of message M3 and M5 to reflect the net effect (namely,increase the quantity of M1 by 8 units). Separately, compressor 1002then processes the modified messages and increases the quantity of M1 by8 units if M1 is still in the buffer 1202.

Compressor 1002 may also net multiple messages from the same source.FIG. 13A illustrates example buffer 1302 holding electronic datatransaction request messages M1 through M6. Buffer 1302 may be similarto buffer 502 described herein. Buffer 1302 includes positions 1 through6, where the first message received is stored in position 1, the secondmessage received is stored in position 2, etc. In one embodiment,interval processor 504 determines that electronic data transactionrequest messages M1 through M6 should be grouped together as describedherein. Each of the positions may be associated with a pointer, whichmay be used to control the order in which messages in the same group areactually forwarded to and processed by the match engine module.

As shown in FIG. 13A, messages M1, M3, M5 and M6 are all related tofinancial instrument FC2. Compressor 1002 determines that messages M1,M3, M5 and M6 all relate to acquiring or relinquishing a quantity of thesame instrument at the same price. Compressor 1002 may determine thatbuy and sell messages can cancel each other out, if the associated priceand quantities are the same. Compressor 1002 compresses or nets theeffects of M1, M3, M5 and M6, and modifies one of the messages toreflect the net effects and deletes all the other messages. As shown inFIG. 13B, compressor 1002 has modified M1 to reflect the net effects ofM1, M3, M5 and M6. In particular, electronic data transaction requestmessage M1 is associated with a quantity of 10 in FIG. 13B. Compressor1002 accordingly has compressed the electronic data transaction requestmessages in buffer 1302 from six messages to three messages.

Instead of compressing M1, M3, M5 and M6 into M1 as shown in FIG. 13B,compressor 1002 may compress M1, M3, M5 and M6 into M3 as shown in FIG.13C. Comparing FIGS. 13 B to 13C, it should be appreciated that thecompression used by compressor 1002 can affect whether the message thatis left in the buffer 1302 (M1 in FIG. 13B, M3 in FIG. 13C) isprioritized before or after other messages in the buffer 1302, such asM2. For example, in FIG. 13B, message M1 may be prioritized beforemessage M2. In FIG. 13C, message M2 may be prioritized before messageM3. Thus, when a source, e.g., T1, submits multiple messages to the datatransaction processing system that are related to the same financialinstrument, if the messages are netted or compressed together, theresulting message may experience a different priority depending on howthe messages are netted and whether other intervening messages (e.g.,M2) exist in the buffer 1302 between netted messages M1 and M3.

It should be appreciated that in one embodiment, compressor 1002 doesnot comprise messages based solely on performing a requestedtransaction. For example, compressor 1002 instead also compresses basedon whether two messages are redundant or duplicative to each other.Compressor 1002 also does not require that messages that are compressedrefer to another electronic data transaction request message. Forinstance, multiple messages requesting that the hardware matchingprocessor perform an action on the same financial instrument may becompressed by the compressor 1002.

In one embodiment, the compressor 1002 may collapse electronic datatransaction request messages from different sources into a fewer numberof electronic data transaction request messages (e.g., one) if theelectronic data transaction request messages all include requests tocreate a same instrument or spread. For example, multiple electronicdata transaction request messages from different sources may requestcreation of a same user-defined-spread (“UDS”). The compressor 1002 maycombine all the user defined spread creation electronic data transactionrequest messages into a single electronic data transaction requestmessage that instructs the match engine module to create the userdefined spread.

In one embodiment, the compressor 1002 may compress messages frommultiple different sources by identifying certain messages types (e.g.,FAK) from different sources, and only choosing to process one and deletethe others.

FIG. 14 illustrates an example computer implemented method 1400 forprocessing electronic data transaction request messages in a datatransaction processing system in which data objects are transacted bytransaction processors that match electronic data transaction requestmessages for data objects received from different client computers overa data communications network. Embodiments may involve all, more orfewer actions indicated by the actions of FIG. 14. The actions may beperformed in the order or sequence shown or in a different sequence.

At step 1402, method 1400 includes storing electronic data transactionrequest messages received by the data transaction processing systemwithin a time interval in a buffer.

At step 1404, method 1400 includes compressing the electronic datatransaction request messages in the buffer based on characteristics ofthe electronic data transaction request messages in the buffer. Asdiscussed herein, characteristics may include an electronic datatransaction request message source; an electronic data transactionrequest message type; an electronic data transaction request messagetransaction type; a value; or a data object. Characteristics may alsoinclude the contents of the transaction request.

At step 1406, method 1400 includes forwarding the electronic datatransaction request messages in the buffer to a hardware matchingprocessor. In one embodiment, the message management module includes atransmitter that transmits or forwards messages from the buffer to thehardware matching processor.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. Many otherembodiments may be apparent to those of skill in the art upon reviewingthe disclosure. Other embodiments may be utilized and derived from thedisclosure, such that structural and logical substitutions and changesmay be made without departing from the scope of the disclosure.Additionally, the illustrations are merely representational and may notbe drawn to scale. Certain proportions within the illustrations may beexaggerated, while other proportions may be minimized. Accordingly, thedisclosure and the figures are to be regarded as illustrative ratherthan restrictive.

While this specification contains many specifics, these should not beconstrued as limitations on the scope of the invention or of what may beclaimed, but rather as descriptions of features specific to particularembodiments of the invention. Certain features that are described inthis specification in the context of separate embodiments can also beimplemented in combination in a single embodiment. Conversely, variousfeatures that are described in the context of a single embodiment canalso be implemented in multiple embodiments separately or in anysuitable sub-combination. Moreover, although features may be describedas acting in certain combinations and even initially claimed as such,one or more features from a claimed combination can in some cases beexcised from the combination, and the claimed combination may bedirected to a sub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings and describedherein in a particular order, this should not be understood as requiringthat such operations be performed in the particular order shown or insequential order, or that all illustrated operations be performed, toachieve desirable results. In certain circumstances, multitasking andparallel processing may be advantageous. Moreover, the separation ofvarious system components in the described embodiments should not beunderstood as requiring such separation in all embodiments, and itshould be understood that the described program components and systemscan generally be integrated together in a single software product orpackaged into multiple software products.

One or more embodiments of the disclosure may be referred to herein,individually, and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b) and is submitted with the understanding that it will not be usedto interpret or limit the scope or meaning of the claims. In addition,in the foregoing Detailed Description, various features may be groupedtogether or described in a single embodiment for the purpose ofstreamlining the disclosure. This disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may be directed toless than all of the features of any of the disclosed embodiments. Thus,the following claims are incorporated into the Detailed Description,with each claim standing on its own as defining separately claimedsubject matter.

It is therefore intended that the foregoing detailed description beregarded as illustrative rather than limiting, and that it be understoodthat it is the following claims, including all equivalents, that areintended to define the spirit and scope of this invention.

What is claimed is:
 1. A computer implemented method for mitigatingdisparities in latencies of electronic data transaction request messagesby a data transaction processing system, the method comprising:determining, by a processor, an interval to be applied to one or moreelectronic data transaction request messages received by and stored in afirst sequence in a buffer coupled with the processor; beginning, by theprocessor, the interval upon receipt of an electronic data transactionrequest message by the buffer; extending, by the processor, the intervalby a per extension time for each subsequent electronic data transactionrequest message received by the buffer before the interval expires; andforwarding, by the processor after the elapse of the interval or amaximum interval time, the electronic data transaction request messagesstored in the buffer to a hardware matching processor in a secondsequence different from the first sequence of reception at the buffer,such that at least one electronic data transaction request messagereceived by the data transaction processing system after anotherelectronic data transaction request message is processed by the hardwarematching processor before the another electronic data transactionrequest message.
 2. The computer implemented method of claim 1, whereinforwarding further comprises: after reaching a maximum extension numberof electronic data transaction request messages in the interval,forwarding, by the processor, the electronic data transaction requestmessages in the buffer to the hardware matching processor.
 3. Thecomputer implemented method of claim 1, wherein each electronic datatransaction request message comprises a request to perform a transactionon a data object, a quantity, and a value.
 4. The computer implementedmethod of claim 1, wherein the second sequence includes electronic datatransaction request messages grouped by electronic data transactionrequest message type.
 5. The computer implemented method of claim 1,wherein the second sequence includes, within each group of electronicdata transaction request messages, electronic data transaction requestmessages arranged in reverse of the order in which the electronic datatransaction request messages were received by the data transactionprocessing system.
 6. The computer implemented method of claim 1,wherein the second sequence is sequenced at least in part oncharacteristics of the electronic data transaction request messages. 7.The computer implemented method of claim 6, wherein the characteristicsinclude at least one of: an electronic data transaction request messagesource; an electronic data transaction request message transaction type;an electronic data transaction request message type; a value; a dataobject; or electronic data transaction request message contents.
 8. Thecomputer implemented method of claim 7, wherein the electronic datatransaction request message transaction type includes one of acquiringor relinquishing a quantity of a data object.
 9. The computerimplemented method of claim 7, wherein the data transaction processingsystem is an exchange computing system, and wherein the data object isassociated with a financial instrument traded in the exchange computingsystem.
 10. The computer implemented method of claim 1, furthercomprising determining, by the processor, the interval, the maximuminterval time, and the per extension time randomly.
 11. The computerimplemented method of claim 2, further comprising determining themaximum extension number of electronic data transaction request messagesrandomly.
 12. A computer system for mitigating disparities in latenciesof electronic data transaction request messages by a data transactionprocessing system, the computer system comprising: a transactionreceiver configured to receive an electronic data transaction requestmessage and store the electronic data transaction request message in abuffer; an interval processor configured to determine an interval havingan extendible interval duration after the reception of the electronicdata transaction request message and for each electronic datatransaction request message received by the transaction receiver afterthe before an elapse of the interval, extend the interval duration by aper extension time up to a maximum interval duration; the buffer coupledto the interval processor and configured to store electronic datatransaction request messages received by the transaction receiver in afirst sequence based on an order in which the electronic datatransaction request messages were received by the transaction receiver;a sequencer coupled to the buffer that, upon the elapse of the interval,is configured to sequence the electronic data transaction requestmessages stored in the buffer in a second sequence different from thefirst sequence; and a hardware matching processor coupled to the bufferconfigured to process the electronic data transaction request messagesin the second sequence, such that at least one electronic datatransaction request message received by the transaction receiver afteranother electronic data transaction request message is processed by thehardware matching processor before the another electronic datatransaction request message.
 13. The computer system of claim 12,wherein each electronic data transaction request message comprises arequest to perform a transaction on a data object, a quantity, and avalue.
 14. The computer system of claim 12, wherein the second sequenceincludes electronic data transaction request messages grouped byelectronic data transaction request message type.
 15. The computersystem of claim 14, wherein the second sequence is based at least inpart on characteristics of an electronic data transaction requestmessage type.
 16. The computer system of claim 15, wherein theelectronic data transaction request message type includes one of limit,fill and kill, or cancel.
 17. The computer system of claim 12, whereinthe interval processor is further configured to determine the interval,the maximum interval duration and the per extension time randomly foreach interval.
 18. The computer system of claim 12, further comprising:a compressor coupled to the buffer that compresses the electronic datatransaction request messages in the buffer based on characteristics ofthe electronic data transaction request messages in the buffer.
 19. Thecomputer system of claim 12, wherein the interval processor is furtherconfigured to forward the electronic data transaction request messagesin the buffer to the hardware matching processor after reaching amaximum extension number of electronic data transaction request messagesin the interval.
 20. A computer system for mitigating disparities inlatencies of electronic data transaction request messages in a datatransaction processing system, the system comprising: means fordetermining an interval to be applied to one or more electronic datatransaction request messages received by and stored in a first sequencein a buffer coupled with the means for determining; means for beginningthe interval upon receipt of an electronic data transaction requestmessage by the buffer; means for extending the interval by a perextension time for each subsequent electronic data transaction requestmessage received by the buffer before the interval expires; and meansfor forwarding, after the elapse of the interval or a maximum intervaltime, the electronic data transaction request messages in the buffer toa hardware matching processor in a second sequence different from thefirst sequence of reception at the buffer, such that at least oneelectronic data transaction request message received by the datatransaction processing system after another electronic data transactionrequest message is processed by the hardware matching processor beforethe another electronic data transaction request message.